From e07a46e94649a18ba9ab348109caf7cc6bf29047 Mon Sep 17 00:00:00 2001
From: Martin H Karrin <martin.h.karrin@captor.se>
Date: Wed, 26 Aug 2026 23:42:09 +0200
Subject: [PATCH 1/4] dependencies update and prepare for plotly 7.0

---
 docs/build/html/.doctrees/environment.pickle  |  Bin 12665956 -> 11799693 bytes
 .../.doctrees/user_guide/installation.doctree |  Bin 24524 -> 24510 bytes
 .../html/_modules/openseries/datefixer.html   |   98 +-
 .../build/html/_modules/openseries/frame.html |  634 ++++----
 .../html/_modules/openseries/load_plotly.html |   26 +-
 .../html/_modules/openseries/owntypes.html    |  356 ++---
 .../_modules/openseries/portfoliotools.html   |  300 ++--
 .../html/_modules/openseries/report.html      |  420 +++---
 .../html/_modules/openseries/series.html      |  262 ++--
 .../html/_modules/openseries/simulation.html  |   86 +-
 .../_sources/user_guide/installation.rst.txt  |    2 +-
 docs/build/html/api/frame.html                |   26 +-
 .../api/generated/openseries.OpenFrame.html   |   12 +-
 .../generated/openseries.OpenTimeSeries.html  |    8 +-
 .../openseries.ReturnSimulation.html          |   12 +-
 docs/build/html/api/series.html               |   18 +-
 docs/build/html/api/simulation.html           |   24 +-
 docs/build/html/api/types.html                |    8 +-
 docs/build/html/development/contributing.html |   90 +-
 docs/build/html/examples/custom_reports.html  |   22 +-
 docs/build/html/examples/multi_asset.html     |  192 +--
 .../html/examples/portfolio_optimization.html |  296 ++--
 docs/build/html/examples/single_asset.html    |  106 +-
 docs/build/html/index.html                    |   16 +-
 .../html/tutorials/advanced_features.html     |  114 +-
 docs/build/html/tutorials/basic_analysis.html |  148 +-
 .../html/tutorials/portfolio_analysis.html    |  296 ++--
 .../build/html/tutorials/risk_management.html |  374 ++---
 docs/build/html/user_guide/core_concepts.html |  110 +-
 docs/build/html/user_guide/data_handling.html |  134 +-
 docs/build/html/user_guide/installation.html  |   10 +-
 docs/build/html/user_guide/quickstart.html    |   90 +-
 docs/source/user_guide/installation.rst       |    2 +-
 openseries/_common_model.py                   |  116 +-
 tests/test_common_model_internals.py          |   57 +-
 uv.lock                                       | 1293 ++++++++++-------
 36 files changed, 3113 insertions(+), 2645 deletions(-)

diff --git a/docs/build/html/.doctrees/environment.pickle b/docs/build/html/.doctrees/environment.pickle
index 21d586f688bc7f2355a4ef2d14140be077d6b992..cc65bea2abac340ddef778ee3573c8d61dd32dee 100644
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diff --git a/docs/build/html/.doctrees/user_guide/installation.doctree b/docs/build/html/.doctrees/user_guide/installation.doctree
index e237b9a1220980d026db28fbddc5d8e7297ba8e9..9313c00022d6dcec2ee9ce837a093e6f69b58786 100644
GIT binary patch
delta 44
zcmV+{0Mq}>zX86#0R(^rm9wz~ixmMZlaLh@ldBb&2_hgUK0P%qF*uW{6&tf|7G6nY
C@D7;(

delta 53
zcmdnDpYhCoMwSNFsRuW*bc-??Po5wu!m49qu4gcLk?1S|O$7}*TT?wl3q1p{;AU5`
GN>2dQ<qwzu

diff --git a/docs/build/html/_modules/openseries/datefixer.html b/docs/build/html/_modules/openseries/datefixer.html
index 39814b84..d17fca60 100644
--- a/docs/build/html/_modules/openseries/datefixer.html
+++ b/docs/build/html/_modules/openseries/datefixer.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;Date related utilities.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""Date related utilities."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -147,12 +147,12 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
     <span class="p">)</span>
 
 <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
-    <span class="s2">&quot;date_fix&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;date_offset_foll&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;generate_calendar_date_range&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;get_previous_business_day_before_today&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;holiday_calendar&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;offset_business_days&quot;</span><span class="p">,</span>
+    <span class="s2">"date_fix"</span><span class="p">,</span>
+    <span class="s2">"date_offset_foll"</span><span class="p">,</span>
+    <span class="s2">"generate_calendar_date_range"</span><span class="p">,</span>
+    <span class="s2">"get_previous_business_day_before_today"</span><span class="p">,</span>
+    <span class="s2">"holiday_calendar"</span><span class="p">,</span>
+    <span class="s2">"offset_business_days"</span><span class="p">,</span>
 <span class="p">]</span>
 
 
@@ -161,7 +161,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
     <span class="n">endyear</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Return a list of holiday dates mapping to list of markets closed.</span>
+<span class="w">    </span><span class="sd">"""Return a list of holiday dates mapping to list of markets closed.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        startyear: First year (inclusive) to consider.</span>
@@ -174,15 +174,15 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="sd">    Raises:</span>
 <span class="sd">        MarketsNotStringNorListStrError: If any market code is not supported by</span>
 <span class="sd">            ``exchange_calendars`` or the input is not a string or list of strings.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">market_list</span> <span class="o">=</span> <span class="p">[</span><span class="n">markets</span><span class="p">]</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">markets</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">else</span> <span class="nb">list</span><span class="p">(</span><span class="n">markets</span><span class="p">)</span>
 
     <span class="n">supported</span> <span class="o">=</span> <span class="n">exchcal</span><span class="o">.</span><span class="n">get_calendar_names</span><span class="p">()</span>
 
     <span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="n">m</span> <span class="ow">in</span> <span class="n">supported</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">market_list</span><span class="p">):</span>
         <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="s2">&quot;Argument markets must be a string market code or a list of market &quot;</span>
-            <span class="s2">&quot;codes supported by exchange_calendars.&quot;</span>
+            <span class="s2">"Argument markets must be a string market code or a list of market "</span>
+            <span class="s2">"codes supported by exchange_calendars."</span>
         <span class="p">)</span>
         <span class="k">raise</span> <span class="n">MarketsNotStringNorListStrError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -191,7 +191,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="n">cal</span> <span class="o">=</span> <span class="n">exchcal</span><span class="o">.</span><span class="n">get_calendar</span><span class="p">(</span><span class="n">m</span><span class="p">)</span>
         <span class="n">cal_hols</span> <span class="o">=</span> <span class="n">cal</span><span class="o">.</span><span class="n">regular_holidays</span><span class="o">.</span><span class="n">holidays</span><span class="p">()</span>
         <span class="n">my_hols</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="n">date</span><span class="o">.</span><span class="n">date</span><span class="p">()</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span>
+            <span class="n">date</span><span class="o">.</span><span class="n">date</span><span class="p">()</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span>
             <span class="k">for</span> <span class="n">date</span> <span class="ow">in</span> <span class="n">cal_hols</span>
             <span class="k">if</span> <span class="p">(</span><span class="n">startyear</span> <span class="o">&lt;=</span> <span class="n">date</span><span class="o">.</span><span class="n">date</span><span class="p">()</span><span class="o">.</span><span class="n">year</span> <span class="o">&lt;=</span> <span class="n">endyear</span><span class="p">)</span>
         <span class="p">]</span>
@@ -205,17 +205,17 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="k">def</span><span class="w"> </span><span class="nf">holiday_calendar</span><span class="p">(</span>
     <span class="n">startyear</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
     <span class="n">endyear</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">busdaycalendar</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate a business calendar.</span>
+<span class="w">    </span><span class="sd">"""Generate a business calendar.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        startyear: First year in date range generated.</span>
 <span class="sd">        endyear: Last year in date range generated.</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">        custom_holidays: Argument where missing holidays can be added.</span>
 
@@ -225,7 +225,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="sd">    Raises:</span>
 <span class="sd">        CountriesNotStringNorListStrError: If ``countries`` is not a supported</span>
 <span class="sd">            ISO 3166-1 alpha-2 string or a list of such strings.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">startyear</span> <span class="o">-=</span> <span class="mi">1</span>
     <span class="n">endyear</span> <span class="o">+=</span> <span class="mi">1</span>
     <span class="k">if</span> <span class="n">startyear</span> <span class="o">==</span> <span class="n">endyear</span><span class="p">:</span>
@@ -243,11 +243,11 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="k">for</span> <span class="n">country</span> <span class="ow">in</span> <span class="n">countries</span><span class="p">:</span>
             <span class="n">staging</span> <span class="o">=</span> <span class="n">country_holidays</span><span class="p">(</span><span class="n">country</span><span class="o">=</span><span class="n">country</span><span class="p">,</span> <span class="n">years</span><span class="o">=</span><span class="n">years</span><span class="p">)</span>
             <span class="n">countryholidays</span> <span class="o">+=</span> <span class="nb">list</span><span class="p">(</span><span class="n">staging</span><span class="p">)</span>
-        <span class="n">hols</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;list[dt.date]&quot;</span><span class="p">,</span> <span class="nb">list</span><span class="p">(</span><span class="n">countryholidays</span><span class="p">))</span>
+        <span class="n">hols</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"list[dt.date]"</span><span class="p">,</span> <span class="nb">list</span><span class="p">(</span><span class="n">countryholidays</span><span class="p">))</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="s2">&quot;Argument countries must be a string country code or &quot;</span>
-            <span class="s2">&quot;a list of string country codes according to ISO 3166-1 alpha-2.&quot;</span>
+            <span class="s2">"Argument countries must be a string country code or "</span>
+            <span class="s2">"a list of string country codes according to ISO 3166-1 alpha-2."</span>
         <span class="p">)</span>
         <span class="k">raise</span> <span class="n">CountriesNotStringNorListStrError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -268,7 +268,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="p">)</span>
         <span class="n">hols</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">date_fix</span><span class="p">(</span><span class="n">fixerdate</span><span class="o">=</span><span class="n">ddate</span><span class="p">)</span> <span class="k">for</span> <span class="n">ddate</span> <span class="ow">in</span> <span class="n">custom_list</span><span class="p">])</span>
 
-    <span class="k">return</span> <span class="n">busdaycalendar</span><span class="p">(</span><span class="n">holidays</span><span class="o">=</span><span class="n">array</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">hols</span><span class="p">)),</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;datetime64[D]&quot;</span><span class="p">))</span></div>
+    <span class="k">return</span> <span class="n">busdaycalendar</span><span class="p">(</span><span class="n">holidays</span><span class="o">=</span><span class="n">array</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">hols</span><span class="p">)),</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">"datetime64[D]"</span><span class="p">))</span></div>
 
 
 
@@ -277,7 +277,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="k">def</span><span class="w"> </span><span class="nf">date_fix</span><span class="p">(</span>
     <span class="n">fixerdate</span><span class="p">:</span> <span class="n">DateType</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Parse different date formats into datetime.date.</span>
+<span class="w">    </span><span class="sd">"""Parse different date formats into datetime.date.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        fixerdate: The data item to parse.</span>
@@ -287,18 +287,18 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 
 <span class="sd">    Raises:</span>
 <span class="sd">        TypeError: If the provided ``fixerdate`` type is not supported.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Unknown date format </span><span class="si">{</span><span class="n">fixerdate</span><span class="si">!s}</span><span class="s2"> of type </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">)</span><span class="si">!s}</span><span class="s2"> encountered&quot;</span>
+<span class="sd">    """</span>
+    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Unknown date format </span><span class="si">{</span><span class="n">fixerdate</span><span class="si">!s}</span><span class="s2"> of type </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">)</span><span class="si">!s}</span><span class="s2"> encountered"</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="n">Timestamp</span> <span class="o">|</span> <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="p">):</span>
         <span class="k">return</span> <span class="n">fixerdate</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">):</span>
         <span class="k">return</span> <span class="n">fixerdate</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="n">datetime64</span><span class="p">):</span>
         <span class="k">return</span> <span class="p">(</span>
-            <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">)[:</span><span class="mi">10</span><span class="p">],</span> <span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">astimezone</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
+            <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">)[:</span><span class="mi">10</span><span class="p">],</span> <span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span><span class="o">.</span><span class="n">astimezone</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
         <span class="p">)</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
-        <span class="k">return</span> <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">astimezone</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
+        <span class="k">return</span> <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="n">fixerdate</span><span class="p">,</span> <span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span><span class="o">.</span><span class="n">astimezone</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
     <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span></div>
 
 
@@ -308,20 +308,20 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="k">def</span><span class="w"> </span><span class="nf">date_offset_foll</span><span class="p">(</span>
     <span class="n">raw_date</span><span class="p">:</span> <span class="n">DateType</span><span class="p">,</span>
     <span class="n">months_offset</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">12</span><span class="p">,</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">adjust</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="n">following</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Offset dates according to a given calendar.</span>
+<span class="w">    </span><span class="sd">"""Offset dates according to a given calendar.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        raw_date: The date to offset from.</span>
 <span class="sd">        months_offset: Number of months as integer. Defaults to 12.</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">        custom_holidays: Argument where missing holidays can be added.</span>
 <span class="sd">        adjust: Determines if offset should adjust for business days.</span>
@@ -331,7 +331,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Offset date.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">raw_date</span> <span class="o">=</span> <span class="n">date_fix</span><span class="p">(</span><span class="n">raw_date</span><span class="p">)</span>
     <span class="n">month_delta</span> <span class="o">=</span> <span class="n">relativedelta</span><span class="p">(</span><span class="n">months</span><span class="o">=</span><span class="n">months_offset</span><span class="p">)</span>
 
@@ -360,22 +360,22 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/generated/openseries.get_previous_business_day_before_today.html#openseries.datefixer.get_previous_business_day_before_today">[docs]</a>
 <span class="k">def</span><span class="w"> </span><span class="nf">get_previous_business_day_before_today</span><span class="p">(</span>
     <span class="n">today</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Bump date backwards to find the previous business day.</span>
+<span class="w">    </span><span class="sd">"""Bump date backwards to find the previous business day.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        today: Manual input of the day from where the previous business day is found.</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">        custom_holidays: Argument where missing holidays can be added.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The previous business day.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">today</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">today</span> <span class="o">=</span> <span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()</span><span class="o">.</span><span class="n">astimezone</span><span class="p">()</span><span class="o">.</span><span class="n">date</span><span class="p">()</span>
 
@@ -396,11 +396,11 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="k">def</span><span class="w"> </span><span class="nf">offset_business_days</span><span class="p">(</span>
     <span class="n">ddate</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">,</span>
     <span class="n">days</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Bump date by business days.</span>
+<span class="w">    </span><span class="sd">"""Bump date by business days.</span>
 
 <span class="sd">    It first adjusts to a valid business day and then bumps with given</span>
 <span class="sd">    number of business days from there.</span>
@@ -411,13 +411,13 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="sd">            that is given.</span>
 <span class="sd">            If days is set as anything other than an integer its value is set to zero.</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">        custom_holidays: Argument where missing holidays can be added.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The new offset business day.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">try</span><span class="p">:</span>
         <span class="n">days</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">days</span><span class="p">)</span>
     <span class="k">except</span> <span class="ne">TypeError</span><span class="p">:</span>
@@ -468,7 +468,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 
     <span class="n">idx</span> <span class="o">=</span> <span class="n">where</span><span class="p">(</span><span class="n">array</span><span class="p">(</span><span class="n">local_bdays</span><span class="p">)</span> <span class="o">==</span> <span class="n">ddate</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
 
-    <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;dt.date&quot;</span><span class="p">,</span> <span class="n">local_bdays</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">days</span><span class="p">])</span></div>
+    <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"dt.date"</span><span class="p">,</span> <span class="n">local_bdays</span><span class="p">[</span><span class="n">idx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">days</span><span class="p">])</span></div>
 
 
 
@@ -478,26 +478,26 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
     <span class="n">trading_days</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
     <span class="n">start</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">end</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate a list of business day calendar dates.</span>
+<span class="w">    </span><span class="sd">"""Generate a list of business day calendar dates.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        trading_days: Number of days to generate. Must be greater than zero.</span>
 <span class="sd">        start: Date when the range starts.</span>
 <span class="sd">        end: Date when the range ends.</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">        custom_holidays: Argument where missing holidays can be added.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        List of business day calendar dates.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">trading_days</span> <span class="o">&lt;</span> <span class="mi">1</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Argument trading_days must be greater than zero.&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Argument trading_days must be greater than zero."</span>
         <span class="k">raise</span> <span class="n">TradingDaysNotAboveZeroError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="k">if</span> <span class="n">start</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">end</span><span class="p">:</span>
@@ -513,7 +513,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="n">tmp_range</span> <span class="o">=</span> <span class="n">date_range</span><span class="p">(</span>
             <span class="n">start</span><span class="o">=</span><span class="n">adjusted_start</span><span class="p">,</span>
             <span class="n">periods</span><span class="o">=</span><span class="n">trading_days</span> <span class="o">*</span> <span class="mi">365</span> <span class="o">//</span> <span class="mi">252</span><span class="p">,</span>
-            <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;D&quot;</span><span class="p">,</span>
+            <span class="n">freq</span><span class="o">=</span><span class="s2">"D"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">calendar</span> <span class="o">=</span> <span class="n">holiday_calendar</span><span class="p">(</span>
             <span class="n">startyear</span><span class="o">=</span><span class="n">adjusted_start</span><span class="o">.</span><span class="n">year</span><span class="p">,</span>
@@ -544,7 +544,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="n">tmp_range</span> <span class="o">=</span> <span class="n">date_range</span><span class="p">(</span>
             <span class="n">end</span><span class="o">=</span><span class="n">adjusted_end</span><span class="p">,</span>
             <span class="n">periods</span><span class="o">=</span><span class="n">trading_days</span> <span class="o">*</span> <span class="mi">365</span> <span class="o">//</span> <span class="mi">252</span><span class="p">,</span>
-            <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;D&quot;</span><span class="p">,</span>
+            <span class="n">freq</span><span class="o">=</span><span class="s2">"D"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">calendar</span> <span class="o">=</span> <span class="n">holiday_calendar</span><span class="p">(</span>
             <span class="n">startyear</span><span class="o">=</span><span class="n">date_fix</span><span class="p">(</span><span class="n">tmp_range</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">year</span><span class="p">,</span>
@@ -563,8 +563,8 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
         <span class="p">]</span>
 
     <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-        <span class="s2">&quot;Provide exactly one of start or end date. &quot;</span>
-        <span class="s2">&quot;Date range is inferred from number of trading days.&quot;</span>
+        <span class="s2">"Provide exactly one of start or end date. "</span>
+        <span class="s2">"Date range is inferred from number of trading days."</span>
     <span class="p">)</span>
     <span class="k">raise</span> <span class="n">BothStartAndEndError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span></div>
 
@@ -577,7 +577,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
     <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">custom_holidays</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DatetimeIndex</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Resample timeseries frequency to business calendar month end dates.</span>
+<span class="w">    </span><span class="sd">"""Resample timeseries frequency to business calendar month end dates.</span>
 
 <span class="sd">    Stubs left in place. Stubs will be aligned to the shortest stub.</span>
 
@@ -591,7 +591,7 @@ <h1>Source code for openseries.datefixer</h1><div class="highlight"><pre>
 <span class="sd">    Returns:</span>
 <span class="sd">        A date range aligned to business period ends.</span>
 
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">copydata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
     <span class="n">copydata</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">copydata</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
     <span class="n">copydata</span> <span class="o">=</span> <span class="n">copydata</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">rule</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span><span class="o">.</span><span class="n">last</span><span class="p">()</span>
diff --git a/docs/build/html/_modules/openseries/frame.html b/docs/build/html/_modules/openseries/frame.html
index 16a0af71..82e91883 100644
--- a/docs/build/html/_modules/openseries/frame.html
+++ b/docs/build/html/_modules/openseries/frame.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;The OpenFrame class.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""The OpenFrame class."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -188,31 +188,31 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="n">logger</span> <span class="o">=</span> <span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;OpenFrame&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"OpenFrame"</span><span class="p">]</span>
 
 
 <div class="viewcode-block" id="OpenFrame">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">OpenFrame</span><span class="p">(</span><span class="n">_CommonModel</span><span class="p">[</span><span class="n">SeriesFloat</span><span class="p">]):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;OpenFrame objects hold OpenTimeSeries in the list constituents.</span>
+<span class="w">    </span><span class="sd">"""OpenFrame objects hold OpenTimeSeries in the list constituents.</span>
 
 <span class="sd">    The intended use is to allow comparisons across these timeseries.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        constituents: List of objects of Class OpenTimeSeries.</span>
 <span class="sd">        weights: List of weights in float format. Optional.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
 
-    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">&quot;constituents&quot;</span><span class="p">)</span>
+    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">"constituents"</span><span class="p">)</span>
     <span class="nd">@classmethod</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_check_labels_unique</span><span class="p">(</span>
         <span class="bp">cls</span><span class="p">:</span> <span class="nb">type</span><span class="p">[</span><span class="n">OpenFrame</span><span class="p">],</span>
         <span class="n">tseries</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">OpenTimeSeries</span><span class="p">],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">OpenTimeSeries</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Pydantic validator ensuring that OpenFrame labels are unique.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Pydantic validator ensuring that OpenFrame labels are unique."""</span>
         <span class="n">labls</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">label</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">tseries</span><span class="p">]</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">labls</span><span class="p">))</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">labls</span><span class="p">):</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;TimeSeries names/labels must be unique&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"TimeSeries names/labels must be unique"</span>
             <span class="k">raise</span> <span class="n">LabelsNotUniqueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">tseries</span>
 
@@ -223,14 +223,14 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">constituents</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">OpenTimeSeries</span><span class="p">],</span>
         <span class="n">weights</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;OpenFrame objects hold OpenTimeSeries in the list constituents.</span>
+<span class="w">        </span><span class="sd">"""OpenFrame objects hold OpenTimeSeries in the list constituents.</span>
 
 <span class="sd">        The intended use is to allow comparisons across these timeseries.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            constituents: List of objects of Class OpenTimeSeries.</span>
 <span class="sd">            weights: List of weights in float format. Optional.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">copied_constituents</span> <span class="o">=</span> <span class="p">[</span><span class="n">ts</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span> <span class="k">for</span> <span class="n">ts</span> <span class="ow">in</span> <span class="n">constituents</span><span class="p">]</span>
 
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span>
@@ -241,16 +241,16 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_set_tsdf</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Set the tsdf DataFrame.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Set the tsdf DataFrame."""</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
             <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
             <span class="k">else</span><span class="p">:</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">concat</span><span class="p">(</span>
-                    <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">tsdf</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span>
+                    <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">tsdf</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span>
                 <span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s2">&quot;OpenFrame() was passed an empty list.&quot;</span><span class="p">)</span>
+            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s2">"OpenFrame() was passed an empty list."</span><span class="p">)</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_coerce_result</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
@@ -261,17 +261,17 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="n">result</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span>
 
 <div class="viewcode-block" id="OpenFrame.from_deepcopy">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.from_deepcopy">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">from_deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create copy of the OpenFrame object.</span>
+<span class="w">        </span><span class="sd">"""Create copy of the OpenFrame object.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></div>
 
 
@@ -279,16 +279,16 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.merge_series">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">merge_series</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
-        <span class="n">how</span><span class="p">:</span> <span class="n">LiteralHowMerge</span> <span class="o">=</span> <span class="s2">&quot;outer&quot;</span><span class="p">,</span>
+        <span class="n">how</span><span class="p">:</span> <span class="n">LiteralHowMerge</span> <span class="o">=</span> <span class="s2">"outer"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Merge index of Pandas Dataframes of the constituent OpenTimeSeries.</span>
+<span class="w">        </span><span class="sd">"""Merge index of Pandas Dataframes of the constituent OpenTimeSeries.</span>
 
 <span class="sd">        Args:</span>
-<span class="sd">            how: The Pandas merge method. Defaults to &quot;outer&quot;.</span>
+<span class="sd">            how: The Pandas merge method. Defaults to "outer".</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">lvl_zero</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">reduce</span><span class="p">(</span>
             <span class="k">lambda</span> <span class="n">left</span><span class="p">,</span> <span class="n">right</span><span class="p">:</span> <span class="n">merge</span><span class="p">(</span>
@@ -306,12 +306,12 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">empty</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;Merging OpenTimeSeries DataFrames with &quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;argument how=</span><span class="si">{</span><span class="n">how</span><span class="si">}</span><span class="s2"> produced an empty DataFrame.&quot;</span>
+                <span class="s2">"Merging OpenTimeSeries DataFrames with "</span>
+                <span class="sa">f</span><span class="s2">"argument how=</span><span class="si">{</span><span class="n">how</span><span class="si">}</span><span class="s2"> produced an empty DataFrame."</span>
             <span class="p">)</span>
             <span class="k">raise</span> <span class="n">MergingResultedInEmptyError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-        <span class="k">if</span> <span class="n">how</span> <span class="o">==</span> <span class="s2">&quot;inner&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">how</span> <span class="o">==</span> <span class="s2">"inner"</span><span class="p">:</span>
             <span class="k">for</span> <span class="n">xerie</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">:</span>
                 <span class="n">xerie</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">xerie</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
         <span class="k">return</span> <span class="bp">self</span></div>
@@ -323,7 +323,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">properties</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">LiteralFrameProps</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate chosen timeseries properties.</span>
+<span class="w">        </span><span class="sd">"""Calculate chosen timeseries properties.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            properties: The properties to calculate. Defaults to calculating all</span>
@@ -331,7 +331,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Properties of the constituent OpenTimeSeries.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="n">properties</span><span class="p">:</span>
             <span class="n">props</span> <span class="o">=</span> <span class="n">OpenFramePropertiesList</span><span class="p">(</span><span class="o">*</span><span class="n">properties</span><span class="p">)</span>
             <span class="n">prop_list</span> <span class="o">=</span> <span class="p">[</span><span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">props</span><span class="p">]</span>
@@ -339,113 +339,113 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">prop_list</span> <span class="o">=</span> <span class="p">[</span>
                 <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">OpenFramePropertiesList</span><span class="o">.</span><span class="n">allowed_strings</span>
             <span class="p">]</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;DataFrame&quot;</span><span class="p">,</span> <span class="n">concat</span><span class="p">(</span><span class="n">prop_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"DataFrame"</span><span class="p">,</span> <span class="n">concat</span><span class="p">(</span><span class="n">prop_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="p">)</span></div>
 
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">lengths_of_items</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of observations of all constituents.</span>
+<span class="w">        </span><span class="sd">"""Number of observations of all constituents.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Number of observations of all constituents.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span> <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">],</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;observations&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"observations"</span><span class="p">,</span>
         <span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">item_count</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of constituents.</span>
+<span class="w">        </span><span class="sd">"""Number of constituents.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Number of constituents.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">)</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">columns_lvl_zero</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Level 0 values of the MultiIndex columns in the .tsdf DataFrame.</span>
+<span class="w">        </span><span class="sd">"""Level 0 values of the MultiIndex columns in the .tsdf DataFrame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Level 0 values of the MultiIndex columns in the .tsdf DataFrame.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">columns_lvl_one</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">ValueType</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Level 1 values of the MultiIndex columns in the .tsdf DataFrame.</span>
+<span class="w">        </span><span class="sd">"""Level 1 values of the MultiIndex columns in the .tsdf DataFrame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Level 1 values of the MultiIndex columns in the .tsdf DataFrame.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">))</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_value_types</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">bool</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Cached value type checks for efficiency.</span>
+<span class="w">        </span><span class="sd">"""Cached value type checks for efficiency.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            List of booleans indicating if each column is ValueType.RTRN.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="p">[</span><span class="n">x</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)]</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">first_indices</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;The first dates in the timeseries of all constituents.</span>
+<span class="w">        </span><span class="sd">"""The first dates in the timeseries of all constituents.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            The first dates in the timeseries of all constituents.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="n">i</span><span class="o">.</span><span class="n">first_idx</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">],</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;first indices&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;datetime64[ns]&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"first indices"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"datetime64[ns]"</span><span class="p">,</span>
         <span class="p">)</span><span class="o">.</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">last_indices</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;The last dates in the timeseries of all constituents.</span>
+<span class="w">        </span><span class="sd">"""The last dates in the timeseries of all constituents.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            The last dates in the timeseries of all constituents.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="n">i</span><span class="o">.</span><span class="n">last_idx</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">],</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;last indices&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;datetime64[ns]&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"last indices"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"datetime64[ns]"</span><span class="p">,</span>
         <span class="p">)</span><span class="o">.</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">span_of_days_all</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of days from the first date to the last for all items in the frame.</span>
+<span class="w">        </span><span class="sd">"""Number of days from the first date to the last for all items in the frame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Number of days from the first date to the last for all</span>
 <span class="sd">            items in the frame.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="n">c</span><span class="o">.</span><span class="n">span_of_days</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">],</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;span of days&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"span of days"</span><span class="p">,</span>
         <span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
 
 <div class="viewcode-block" id="OpenFrame.value_to_ret">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.value_to_ret">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">value_to_ret</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of values into series of returns.</span>
+<span class="w">        </span><span class="sd">"""Convert series of values into series of returns.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            The returns of the values in the series.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
         <span class="n">returns</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="n">new_labels</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">ValueType</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">item_count</span>
         <span class="n">arrays</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;Any&quot;</span><span class="p">,</span>
+            <span class="s2">"Any"</span><span class="p">,</span>
             <span class="p">[</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span>
                 <span class="n">new_labels</span><span class="p">,</span>
@@ -459,7 +459,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenFrame.value_to_diff">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.value_to_diff">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">value_to_diff</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">periods</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of values to series of their period differences.</span>
+<span class="w">        </span><span class="sd">"""Convert series of values to series of their period differences.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            periods: The number of periods between observations over which</span>
@@ -467,12 +467,12 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">periods</span><span class="o">=</span><span class="n">periods</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="n">new_labels</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">ValueType</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">item_count</span>
         <span class="n">arrays</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;Any&quot;</span><span class="p">,</span>
+            <span class="s2">"Any"</span><span class="p">,</span>
             <span class="p">[</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span>
                 <span class="n">new_labels</span><span class="p">,</span>
@@ -485,11 +485,11 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenFrame.to_cumret">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.to_cumret">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">to_cumret</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of returns into cumulative series of values.</span>
+<span class="w">        </span><span class="sd">"""Convert series of returns into cumulative series of values.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="n">returns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
@@ -498,7 +498,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">returns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
             <span class="n">returns</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
             <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
         <span class="n">returns</span> <span class="o">=</span> <span class="n">returns</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span>
@@ -506,7 +506,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
         <span class="n">new_labels</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">ValueType</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">item_count</span>
         <span class="n">arrays</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;Any&quot;</span><span class="p">,</span>
+            <span class="s2">"Any"</span><span class="p">,</span>
             <span class="p">[</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span>
                 <span class="n">new_labels</span><span class="p">,</span>
@@ -520,24 +520,24 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.resample">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">resample</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
-        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;BME&quot;</span><span class="p">,</span>
+        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"BME"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Resample the timeseries frequency.</span>
+<span class="w">        </span><span class="sd">"""Resample the timeseries frequency.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            freq: The date offset string that sets the resampled frequency.</span>
-<span class="sd">                Defaults to &quot;BME&quot;.</span>
+<span class="sd">                Defaults to "BME".</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="n">value_type</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span>
         <span class="k">elif</span> <span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="n">value_type</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
             <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
@@ -561,28 +561,28 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.resample_to_business_period_ends">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">resample_to_business_period_ends</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
-        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">&quot;BME&quot;</span><span class="p">,</span>
-        <span class="n">method</span><span class="p">:</span> <span class="n">LiteralPandasReindexMethod</span> <span class="o">=</span> <span class="s2">&quot;nearest&quot;</span><span class="p">,</span>
+        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">"BME"</span><span class="p">,</span>
+        <span class="n">method</span><span class="p">:</span> <span class="n">LiteralPandasReindexMethod</span> <span class="o">=</span> <span class="s2">"nearest"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Resamples timeseries frequency to the business calendar month end dates.</span>
+<span class="w">        </span><span class="sd">"""Resamples timeseries frequency to the business calendar month end dates.</span>
 
 <span class="sd">        Stubs left in place. Stubs will be aligned to the shortest stub.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            freq: The date offset string that sets the resampled frequency.</span>
-<span class="sd">                Defaults to &quot;BME&quot;.</span>
+<span class="sd">                Defaults to "BME".</span>
 <span class="sd">            method: Controls the method used to align values across columns.</span>
 <span class="sd">                Defaults to nearest.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;Do not run resample_to_business_period_ends on return series. &quot;</span>
-                <span class="s2">&quot;The operation will pick the last data point in the sparser series. &quot;</span>
-                <span class="s2">&quot;It will not sum returns and therefore data will be lost.&quot;</span>
+                <span class="s2">"Do not run resample_to_business_period_ends on return series. "</span>
+                <span class="s2">"The operation will pick the last data point in the sparser series. "</span>
+                <span class="s2">"It will not sum returns and therefore data will be lost."</span>
             <span class="p">)</span>
             <span class="k">raise</span> <span class="n">ResampleDataLossError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -625,7 +625,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Exponentially Weighted Moving Average Volatilities and Correlation.</span>
+<span class="w">        </span><span class="sd">"""Exponentially Weighted Moving Average Volatilities and Correlation.</span>
 
 <span class="sd">        Exponentially Weighted Moving Average (EWMA) for Volatilities and</span>
 <span class="sd">        Correlation.</span>
@@ -649,7 +649,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Series volatilities and correlation.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
             <span class="n">from_dt</span><span class="o">=</span><span class="n">from_date</span><span class="p">,</span>
@@ -658,7 +658,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">periods_in_a_year_fixed</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">fraction</span> <span class="o">=</span> <span class="p">(</span><span class="n">later</span> <span class="o">-</span> <span class="n">earlier</span><span class="p">)</span><span class="o">.</span><span class="n">days</span> <span class="o">/</span> <span class="mf">365.25</span>
             <span class="n">how_many</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)]</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)]</span>
                 <span class="o">.</span><span class="n">count</span><span class="p">()</span>
                 <span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
             <span class="p">)</span>
@@ -667,17 +667,17 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">time_factor</span> <span class="o">=</span> <span class="n">periods_in_a_year_fixed</span>
 
         <span class="n">corr_label</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-            <span class="o">+</span> <span class="s2">&quot;_VS_&quot;</span>
-            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="o">+</span> <span class="s2">"_VS_"</span>
+            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="p">)</span>
         <span class="n">cols</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
         <span class="p">]</span>
 
         <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
         <span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
 
         <span class="k">for</span> <span class="n">rtn</span> <span class="ow">in</span> <span class="n">cols</span><span class="p">:</span>
@@ -740,25 +740,25 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">correl_matrix</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Correlation matrix.</span>
+<span class="w">        </span><span class="sd">"""Correlation matrix.</span>
 
 <span class="sd">        This property returns the correlation matrix of the time series</span>
 <span class="sd">        in the frame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Correlation matrix of the time series in the frame.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">corr_matrix</span> <span class="o">=</span> <span class="p">(</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span>
             <span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
             <span class="o">.</span><span class="n">corr</span><span class="p">(</span>
-                <span class="n">method</span><span class="o">=</span><span class="s2">&quot;pearson&quot;</span><span class="p">,</span>
+                <span class="n">method</span><span class="o">=</span><span class="s2">"pearson"</span><span class="p">,</span>
                 <span class="n">min_periods</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
             <span class="p">)</span>
         <span class="p">)</span>
         <span class="n">corr_matrix</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">corr_matrix</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
         <span class="n">corr_matrix</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">corr_matrix</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-        <span class="n">corr_matrix</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Correlation&quot;</span>
+        <span class="n">corr_matrix</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Correlation"</span>
         <span class="k">return</span> <span class="n">corr_matrix</span>
 
 <div class="viewcode-block" id="OpenFrame.add_timeseries">
@@ -767,30 +767,30 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">new_series</span><span class="p">:</span> <span class="n">OpenTimeSeries</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;To add an OpenTimeSeries object.</span>
+<span class="w">        </span><span class="sd">"""To add an OpenTimeSeries object.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            new_series: The timeseries to add.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span> <span class="o">+=</span> <span class="p">[</span><span class="n">new_series</span><span class="p">]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">concat</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">,</span> <span class="n">new_series</span><span class="o">.</span><span class="n">tsdf</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">concat</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">,</span> <span class="n">new_series</span><span class="o">.</span><span class="n">tsdf</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
         <span class="k">return</span> <span class="bp">self</span></div>
 
 
 <div class="viewcode-block" id="OpenFrame.delete_timeseries">
 <a class="viewcode-back" href="../../api/generated/openseries.OpenFrame.html#openseries.OpenFrame.delete_timeseries">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">delete_timeseries</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">lvl_zero_item</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;To delete an OpenTimeSeries object.</span>
+<span class="w">        </span><span class="sd">"""To delete an OpenTimeSeries object.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lvl_zero_item: The .tsdf column level 0 value of the timeseries to delete.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">:</span>
             <span class="n">new_c</span><span class="p">,</span> <span class="n">new_w</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
             <span class="k">for</span> <span class="n">serie</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
@@ -803,7 +803,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span> <span class="o">=</span> <span class="p">[</span>
                 <span class="n">item</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="n">item</span><span class="o">.</span><span class="n">label</span> <span class="o">!=</span> <span class="n">lvl_zero_item</span>
             <span class="p">]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">lvl_zero_item</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span> <span class="n">level</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">lvl_zero_item</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span> <span class="n">level</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
         <span class="k">return</span> <span class="bp">self</span></div>
 
 
@@ -813,9 +813,9 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">start_cut</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">end_cut</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">where</span><span class="p">:</span> <span class="n">LiteralTrunc</span> <span class="o">=</span> <span class="s2">&quot;both&quot;</span><span class="p">,</span>
+        <span class="n">where</span><span class="p">:</span> <span class="n">LiteralTrunc</span> <span class="o">=</span> <span class="s2">"both"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Truncate DataFrame such that all timeseries have the same time span.</span>
+<span class="w">        </span><span class="sd">"""Truncate DataFrame such that all timeseries have the same time span.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            start_cut: New first date. Optional.</span>
@@ -825,10 +825,10 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenFrame object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="k">if</span> <span class="ow">not</span> <span class="n">start_cut</span> <span class="ow">and</span> <span class="n">where</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;before&quot;</span><span class="p">,</span> <span class="s2">&quot;both&quot;</span><span class="p">]:</span>
+<span class="sd">        """</span>
+        <span class="k">if</span> <span class="ow">not</span> <span class="n">start_cut</span> <span class="ow">and</span> <span class="n">where</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">"before"</span><span class="p">,</span> <span class="s2">"both"</span><span class="p">]:</span>
             <span class="n">start_cut</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">first_indices</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
-        <span class="k">if</span> <span class="ow">not</span> <span class="n">end_cut</span> <span class="ow">and</span> <span class="n">where</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;after&quot;</span><span class="p">,</span> <span class="s2">&quot;both&quot;</span><span class="p">]:</span>
+        <span class="k">if</span> <span class="ow">not</span> <span class="n">end_cut</span> <span class="ow">and</span> <span class="n">where</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">"after"</span><span class="p">,</span> <span class="s2">"both"</span><span class="p">]:</span>
             <span class="n">end_cut</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">last_indices</span><span class="o">.</span><span class="n">min</span><span class="p">()</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">truncate</span><span class="p">(</span><span class="n">before</span><span class="o">=</span><span class="n">start_cut</span><span class="p">,</span> <span class="n">after</span><span class="o">=</span><span class="n">end_cut</span><span class="p">)</span>
@@ -840,16 +840,16 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="p">)</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">first_indices</span><span class="p">))</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="sa">f</span><span class="s2">&quot;One or more constituents still &quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;not truncated to same start dates.</span><span class="se">\n</span><span class="s2">&quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">head</span><span class="p">()</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="sa">f</span><span class="s2">"One or more constituents still "</span>
+                <span class="sa">f</span><span class="s2">"not truncated to same start dates.</span><span class="se">\n</span><span class="s2">"</span>
+                <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">head</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span>
             <span class="p">)</span>
             <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">last_indices</span><span class="p">))</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="sa">f</span><span class="s2">&quot;One or more constituents still &quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;not truncated to same end dates.</span><span class="se">\n</span><span class="s2">&quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">tail</span><span class="p">()</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="sa">f</span><span class="s2">"One or more constituents still "</span>
+                <span class="sa">f</span><span class="s2">"not truncated to same end dates.</span><span class="se">\n</span><span class="s2">"</span>
+                <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">tail</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span>
             <span class="p">)</span>
             <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="k">return</span> <span class="bp">self</span></div>
@@ -864,18 +864,18 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">base_zero</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate cumulative relative return between two series.</span>
+<span class="w">        </span><span class="sd">"""Calculate cumulative relative return between two series.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            long_column: Column number of timeseries bought. Defaults to 0.</span>
 <span class="sd">            short_column: Column number of timeseries sold. Defaults to 1.</span>
 <span class="sd">            base_zero: If set to False 1.0 is added to allow for a capital base and</span>
 <span class="sd">                to allow a volatility calculation. Defaults to True.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">rel_label</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">long_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-            <span class="o">+</span> <span class="s2">&quot;_over_&quot;</span>
-            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">short_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">long_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="o">+</span> <span class="s2">"_over_"</span>
+            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">short_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="p">)</span>
         <span class="k">if</span> <span class="n">base_zero</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">rel_label</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RELRTRN</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
@@ -900,7 +900,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Tracking Error.</span>
+<span class="w">        </span><span class="sd">"""Tracking Error.</span>
 
 <span class="sd">        Calculates Tracking Error which is the standard deviation of the</span>
 <span class="sd">        difference between the fund and its index returns.</span>
@@ -919,7 +919,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Tracking Errors.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
             <span class="n">from_dt</span><span class="o">=</span><span class="n">from_date</span><span class="p">,</span>
@@ -948,7 +948,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="n">terrors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
                 <span class="n">longdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-                    <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+                    <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
                 <span class="p">][</span><span class="n">item</span><span class="p">]</span>
                 <span class="n">relative</span> <span class="o">=</span> <span class="n">longdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span> <span class="o">-</span> <span class="n">shortdf_returns</span>
                 <span class="n">vol</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">relative</span><span class="o">.</span><span class="n">std</span><span class="p">()</span> <span class="o">*</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">time_factor</span><span class="p">))</span>
@@ -957,8 +957,8 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="n">terrors</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;Tracking Errors vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"Tracking Errors vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -972,7 +972,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Information Ratio.</span>
+<span class="w">        </span><span class="sd">"""Information Ratio.</span>
 
 <span class="sd">        The Information Ratio equals ( fund return less index return ) divided</span>
 <span class="sd">        by the Tracking Error. And the Tracking Error is the standard deviation of</span>
@@ -991,7 +991,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Information Ratios.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
             <span class="n">from_dt</span><span class="o">=</span><span class="n">from_date</span><span class="p">,</span>
@@ -1020,7 +1020,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="n">ratios</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
                 <span class="n">longdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-                    <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+                    <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
                 <span class="p">][</span><span class="n">item</span><span class="p">]</span>
                 <span class="n">relative</span> <span class="o">=</span> <span class="n">longdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span> <span class="o">-</span> <span class="n">shortdf_returns</span>
                 <span class="n">ret</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">relative</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="n">time_factor</span><span class="p">)</span>
@@ -1030,8 +1030,8 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="n">ratios</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;Info Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"Info Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -1041,7 +1041,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">mask</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">bool_</span><span class="p">],</span>
         <span class="n">time_factor</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate CAGR from returns array with mask.</span>
+<span class="w">        </span><span class="sd">"""Calculate CAGR from returns array with mask.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            returns_array: Returns array.</span>
@@ -1050,7 +1050,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            CAGR value.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">masked_array</span> <span class="o">=</span> <span class="n">returns_array</span><span class="p">[</span><span class="n">mask</span><span class="p">]</span> <span class="o">+</span> <span class="mf">1.0</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">masked_array</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
             <span class="k">return</span> <span class="mf">0.0</span>
@@ -1066,7 +1066,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">down_mask</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">bool_</span><span class="p">],</span>
         <span class="n">time_factor</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate capture ratio for a single item.</span>
+<span class="w">        </span><span class="sd">"""Calculate capture ratio for a single item.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            ratio: Ratio type to calculate.</span>
@@ -1081,8 +1081,8 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            RatioInputError: If ratio is invalid.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">&quot;up&quot;</span><span class="p">:</span>
+<span class="sd">        """</span>
+        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">"up"</span><span class="p">:</span>
             <span class="n">up_rtrn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_cagr_from_returns</span><span class="p">(</span>
                 <span class="n">longdf_returns_np</span><span class="p">,</span> <span class="n">up_mask</span><span class="p">,</span> <span class="n">time_factor</span>
             <span class="p">)</span>
@@ -1093,7 +1093,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="k">return</span> <span class="mf">0.0</span>
             <span class="k">return</span> <span class="n">up_rtrn</span> <span class="o">/</span> <span class="n">up_idx_return</span>
 
-        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">&quot;down&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">"down"</span><span class="p">:</span>
             <span class="n">down_return</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_cagr_from_returns</span><span class="p">(</span>
                 <span class="n">longdf_returns_np</span><span class="p">,</span> <span class="n">down_mask</span><span class="p">,</span> <span class="n">time_factor</span>
             <span class="p">)</span>
@@ -1104,7 +1104,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="k">return</span> <span class="mf">0.0</span>
             <span class="k">return</span> <span class="n">down_return</span> <span class="o">/</span> <span class="n">down_idx_return</span>
 
-        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">&quot;both&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">ratio</span> <span class="o">==</span> <span class="s2">"both"</span><span class="p">:</span>
             <span class="n">up_rtrn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_cagr_from_returns</span><span class="p">(</span>
                 <span class="n">longdf_returns_np</span><span class="p">,</span> <span class="n">up_mask</span><span class="p">,</span> <span class="n">time_factor</span>
             <span class="p">)</span>
@@ -1121,7 +1121,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="k">return</span> <span class="mf">0.0</span>
             <span class="k">return</span> <span class="p">(</span><span class="n">up_rtrn</span> <span class="o">/</span> <span class="n">up_idx_return</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">down_return</span> <span class="o">/</span> <span class="n">down_idx_return</span><span class="p">)</span>
 
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;ratio must be one of &#39;up&#39;, &#39;down&#39; or &#39;both&#39;.&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"ratio must be one of 'up', 'down' or 'both'."</span>
         <span class="k">raise</span> <span class="n">RatioInputError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
 <div class="viewcode-block" id="OpenFrame.capture_ratio_func">
@@ -1135,14 +1135,14 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Capture Ratio.</span>
+<span class="w">        </span><span class="sd">"""Capture Ratio.</span>
 
 <span class="sd">        The Up (Down) Capture Ratio is calculated by dividing the CAGR</span>
 <span class="sd">        of the asset during periods that the benchmark returns are positive (negative)</span>
 <span class="sd">        by the CAGR of the benchmark during the same periods.</span>
 <span class="sd">        CaptureRatio.BOTH is the Up ratio divided by the Down ratio.</span>
-<span class="sd">        Source: &#39;Capture Ratios: A Popular Method of Measuring Portfolio Performance</span>
-<span class="sd">        in Practice&#39;, Don R. Cox and Delbert C. Goff, Journal of Economics and</span>
+<span class="sd">        Source: 'Capture Ratios: A Popular Method of Measuring Portfolio Performance</span>
+<span class="sd">        in Practice', Don R. Cox and Delbert C. Goff, Journal of Economics and</span>
 <span class="sd">        Finance Education (Vol 2 Winter 2013).</span>
 
 <span class="sd">        Reference: https://www.economics-finance.org/jefe/volume12-2/11ArticleCox.pdf.</span>
@@ -1160,7 +1160,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Capture Ratios.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">loss_limit</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
@@ -1182,7 +1182,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">time_factor</span> <span class="o">=</span> <span class="n">shortdf</span><span class="o">.</span><span class="n">count</span><span class="p">()</span> <span class="o">/</span> <span class="n">fraction</span>
 
         <span class="n">shortdf_returns</span> <span class="o">=</span> <span class="n">shortdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
-        <span class="n">shortdf_returns_np</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span> <span class="n">shortdf_returns</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">())</span>
+        <span class="n">shortdf_returns_np</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"NDArray[float64]"</span><span class="p">,</span> <span class="n">shortdf_returns</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">())</span>
         <span class="n">up_mask</span> <span class="o">=</span> <span class="n">shortdf_returns_np</span> <span class="o">&gt;</span> <span class="n">loss_limit</span>
         <span class="n">down_mask</span> <span class="o">=</span> <span class="n">shortdf_returns_np</span> <span class="o">&lt;</span> <span class="n">loss_limit</span>
 
@@ -1192,10 +1192,10 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="n">ratios</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
                 <span class="n">longdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-                    <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+                    <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
                 <span class="p">][</span><span class="n">item</span><span class="p">]</span>
                 <span class="n">longdf_returns</span> <span class="o">=</span> <span class="n">longdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
-                <span class="n">longdf_returns_np</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span> <span class="n">longdf_returns</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">())</span>
+                <span class="n">longdf_returns_np</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"NDArray[float64]"</span><span class="p">,</span> <span class="n">longdf_returns</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">())</span>
                 <span class="n">ratio_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_capture_ratio_for_item</span><span class="p">(</span>
                     <span class="n">ratio</span><span class="o">=</span><span class="n">ratio</span><span class="p">,</span>
                     <span class="n">longdf_returns_np</span><span class="o">=</span><span class="n">longdf_returns_np</span><span class="p">,</span>
@@ -1207,9 +1207,9 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                 <span class="n">ratios</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ratio_value</span><span class="p">)</span>
 
         <span class="n">ratio_names</span> <span class="o">=</span> <span class="p">{</span>
-            <span class="s2">&quot;up&quot;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;Up Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;down&quot;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;Down Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;both&quot;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;Up-Down Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
+            <span class="s2">"up"</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"Up Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="s2">"down"</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"Down Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="s2">"both"</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"Up-Down Capture Ratios vs </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
         <span class="p">}</span>
         <span class="n">resultname</span> <span class="o">=</span> <span class="n">ratio_names</span><span class="p">[</span><span class="n">ratio</span><span class="p">]</span>
 
@@ -1217,7 +1217,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="n">ratios</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="n">resultname</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -1225,9 +1225,9 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">column</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">ValueType</span><span class="p">]</span> <span class="o">|</span> <span class="nb">int</span><span class="p">,</span>
         <span class="n">vtypes</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">bool</span><span class="p">],</span>
-        <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;column&quot;</span><span class="p">,</span>
+        <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"column"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Extract column value based on value types.</span>
+<span class="w">        </span><span class="sd">"""Extract column value based on value types.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            column: Column reference.</span>
@@ -1239,8 +1239,8 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            TypeError: If column type is invalid.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">param_name</span><span class="si">}</span><span class="s2"> should be a tuple[str, ValueType] or an integer.&quot;</span>
+<span class="sd">        """</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">param_name</span><span class="si">}</span><span class="s2"> should be a tuple[str, ValueType] or an integer."</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">column</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
             <span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
                 <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">column</span><span class="p">]</span>
@@ -1259,7 +1259,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">market</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">ValueType</span><span class="p">]</span> <span class="o">|</span> <span class="nb">int</span><span class="p">,</span>
         <span class="n">dlta_degr_freedms</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Market Beta.</span>
+<span class="w">        </span><span class="sd">"""Market Beta.</span>
 
 <span class="sd">        Calculates Beta as Co-variance of asset &amp; market divided by Variance</span>
 <span class="sd">        of the market.</span>
@@ -1274,14 +1274,14 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Beta as Co-variance of x &amp; y divided by Variance of x.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">)):</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
             <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-        <span class="n">y_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">&quot;asset&quot;</span><span class="p">)</span>
-        <span class="n">x_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">market</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">&quot;market&quot;</span><span class="p">)</span>
+        <span class="n">y_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">"asset"</span><span class="p">)</span>
+        <span class="n">x_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">market</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">"market"</span><span class="p">)</span>
 
         <span class="n">covariance</span> <span class="o">=</span> <span class="n">cov</span><span class="p">(</span><span class="n">m</span><span class="o">=</span><span class="n">y_value</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">x_value</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="n">dlta_degr_freedms</span><span class="p">)</span>
         <span class="n">beta</span> <span class="o">=</span> <span class="n">covariance</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">/</span> <span class="n">covariance</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span>
@@ -1298,7 +1298,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">fitted_series</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Ordinary Least Squares fit.</span>
+<span class="w">        </span><span class="sd">"""Ordinary Least Squares fit.</span>
 
 <span class="sd">        Performs a linear regression and adds a new column with a fitted line</span>
 <span class="sd">        using Ordinary Least Squares fit.</span>
@@ -1311,30 +1311,30 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            A dictionary with the coefficient, intercept and rsquared outputs.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;y_column should be a tuple[str, ValueType] or an integer.&quot;</span>
+<span class="sd">        """</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"y_column should be a tuple[str, ValueType] or an integer."</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y_column</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
             <span class="n">y_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">y_column</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span>
             <span class="n">y_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span>
+                <span class="s2">"tuple[str, str]"</span><span class="p">,</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">y_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">,</span>
             <span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y_column</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
             <span class="n">y_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">y_column</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span>
-            <span class="n">y_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">y_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">y_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">y_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;x_column should be a tuple[str, ValueType] or an integer.&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"x_column should be a tuple[str, ValueType] or an integer."</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x_column</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
             <span class="n">x_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">x_column</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
             <span class="n">x_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span>
+                <span class="s2">"tuple[str, str]"</span><span class="p">,</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">x_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">,</span>
             <span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x_column</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
             <span class="n">x_value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">x_column</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-            <span class="n">x_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">x_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">x_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">x_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -1343,9 +1343,9 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">fitted_series</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">y_label</span><span class="p">,</span> <span class="n">x_label</span><span class="p">]</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">x_value</span><span class="p">)</span>
         <span class="k">return</span> <span class="p">{</span>
-            <span class="s2">&quot;coefficient&quot;</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">coef_</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
-            <span class="s2">&quot;intercept&quot;</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">intercept_</span><span class="p">),</span>
-            <span class="s2">&quot;rsquared&quot;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">x_value</span><span class="p">,</span> <span class="n">y_value</span><span class="p">),</span>
+            <span class="s2">"coefficient"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">coef_</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
+            <span class="s2">"intercept"</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">intercept_</span><span class="p">),</span>
+            <span class="s2">"rsquared"</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">x_value</span><span class="p">,</span> <span class="n">y_value</span><span class="p">),</span>
         <span class="p">}</span></div>
 
 
@@ -1358,34 +1358,34 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">riskfree_rate</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">dlta_degr_freedms</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Jensen&#39;s alpha.</span>
+<span class="w">        </span><span class="sd">"""Jensen's alpha.</span>
 
-<span class="sd">        The Jensen&#39;s measure, or Jensen&#39;s alpha, is a risk-adjusted performance</span>
+<span class="sd">        The Jensen's measure, or Jensen's alpha, is a risk-adjusted performance</span>
 <span class="sd">        measure that represents the average return on a portfolio or investment,</span>
 <span class="sd">        above or below that predicted by the capital asset pricing model (CAPM),</span>
-<span class="sd">        given the portfolio&#39;s or investment&#39;s beta and the average market return.</span>
+<span class="sd">        given the portfolio's or investment's beta and the average market return.</span>
 <span class="sd">        This metric is also commonly referred to as simply alpha.</span>
 
 <span class="sd">        Reference: https://www.investopedia.com/terms/j/jensensmeasure.asp.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            asset: The column of the asset.</span>
-<span class="sd">            market: The column of the market against which Jensen&#39;s alpha is measured.</span>
+<span class="sd">            market: The column of the market against which Jensen's alpha is measured.</span>
 <span class="sd">            riskfree_rate: The return of the zero volatility riskfree asset.</span>
 <span class="sd">                Defaults to 0.0.</span>
 <span class="sd">            dlta_degr_freedms: Variance bias factor taking the value 0 or 1.</span>
 <span class="sd">                Defaults to 1.</span>
 
 <span class="sd">        Returns:</span>
-<span class="sd">            Jensen&#39;s alpha.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">            Jensen's alpha.</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">)</span> <span class="ow">or</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">)):</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
             <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-        <span class="n">asset_rtn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">&quot;asset&quot;</span><span class="p">)</span>
-        <span class="n">market_rtn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">market</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">&quot;market&quot;</span><span class="p">)</span>
+        <span class="n">asset_rtn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">"asset"</span><span class="p">)</span>
+        <span class="n">market_rtn</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_extract_column_value</span><span class="p">(</span><span class="n">market</span><span class="p">,</span> <span class="n">vtypes</span><span class="p">,</span> <span class="n">param_name</span><span class="o">=</span><span class="s2">"market"</span><span class="p">)</span>
 
         <span class="n">asset_rtn_mean</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">asset_rtn</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="p">)</span>
         <span class="n">market_rtn_mean</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">market_rtn</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="p">)</span>
@@ -1399,14 +1399,14 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_prepare_returns_for_portfolio</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Prepare returns DataFrame for portfolio calculation.</span>
+<span class="w">        </span><span class="sd">"""Prepare returns DataFrame for portfolio calculation.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Returns DataFrame.</span>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            MixedValuetypesError: If series types are mixed.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vtypes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_value_types</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="n">returns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
@@ -1414,32 +1414,32 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="k">return</span> <span class="n">returns</span>
         <span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
         <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_calculate_eq_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate equal weights.</span>
+<span class="w">        </span><span class="sd">"""Calculate equal weights.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            List of equal weights.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="p">[</span><span class="mf">1.0</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">item_count</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">item_count</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_calculate_inv_vol_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">returns</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate inverse volatility weights.</span>
+<span class="w">        </span><span class="sd">"""Calculate inverse volatility weights.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            returns: Returns DataFrame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            List of inverse volatility weights.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vol</span> <span class="o">=</span> <span class="n">divide</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">std</span><span class="p">(</span><span class="n">returns</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
         <span class="n">vol</span><span class="p">[</span><span class="n">isinf</span><span class="p">(</span><span class="n">vol</span><span class="p">)]</span> <span class="o">=</span> <span class="n">nan</span>
         <span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="n">divide</span><span class="p">(</span><span class="n">vol</span><span class="p">,</span> <span class="n">vol</span><span class="o">.</span><span class="n">sum</span><span class="p">()))</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_calculate_max_div_weights</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">returns</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate maximum diversification weights.</span>
+<span class="w">        </span><span class="sd">"""Calculate maximum diversification weights.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            returns: Returns DataFrame.</span>
@@ -1450,12 +1450,12 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <span class="sd">        Raises:</span>
 <span class="sd">            MaxDiversificationNaNError: If correlation matrix has NaN values.</span>
 <span class="sd">            MaxDiversificationNegativeWeightsError: If weights are negative.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">corr_matrix</span> <span class="o">=</span> <span class="n">corrcoef</span><span class="p">(</span><span class="n">returns</span><span class="o">.</span><span class="n">T</span><span class="p">)</span>
         <span class="n">corr_matrix</span><span class="p">[</span><span class="n">isinf</span><span class="p">(</span><span class="n">corr_matrix</span><span class="p">)]</span> <span class="o">=</span> <span class="n">nan</span>
         <span class="n">corr_matrix</span><span class="p">[</span><span class="n">isnan</span><span class="p">(</span><span class="n">corr_matrix</span><span class="p">)]</span> <span class="o">=</span> <span class="n">nan</span>
 
-        <span class="n">msga</span> <span class="o">=</span> <span class="s2">&quot;max_div weight strategy failed: correlation matrix contains NaN values&quot;</span>
+        <span class="n">msga</span> <span class="o">=</span> <span class="s2">"max_div weight strategy failed: correlation matrix contains NaN values"</span>
         <span class="k">if</span> <span class="n">isnan</span><span class="p">(</span><span class="n">corr_matrix</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">():</span>
             <span class="k">raise</span> <span class="n">MaxDiversificationNaNError</span><span class="p">(</span><span class="n">msga</span><span class="p">)</span>
 
@@ -1463,29 +1463,29 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">inv_corr_sum</span> <span class="o">=</span> <span class="n">linalg</span><span class="o">.</span><span class="n">inv</span><span class="p">(</span><span class="n">corr_matrix</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
 
             <span class="n">msgb</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;max_div weight strategy failed: &quot;</span>
-                <span class="s2">&quot;inverse correlation matrix sum contains NaN values&quot;</span>
+                <span class="s2">"max_div weight strategy failed: "</span>
+                <span class="s2">"inverse correlation matrix sum contains NaN values"</span>
             <span class="p">)</span>
             <span class="k">if</span> <span class="n">isnan</span><span class="p">(</span><span class="n">inv_corr_sum</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">():</span>
                 <span class="k">raise</span> <span class="n">MaxDiversificationNaNError</span><span class="p">(</span><span class="n">msgb</span><span class="p">)</span>
 
             <span class="n">weights</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">divide</span><span class="p">(</span><span class="n">inv_corr_sum</span><span class="p">,</span> <span class="n">inv_corr_sum</span><span class="o">.</span><span class="n">sum</span><span class="p">()))</span>
 
-            <span class="n">msgc</span> <span class="o">=</span> <span class="s2">&quot;max_div weight strategy failed: final weights contain NaN values&quot;</span>
+            <span class="n">msgc</span> <span class="o">=</span> <span class="s2">"max_div weight strategy failed: final weights contain NaN values"</span>
             <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">isnan</span><span class="p">(</span><span class="n">weight</span><span class="p">)</span> <span class="k">for</span> <span class="n">weight</span> <span class="ow">in</span> <span class="n">weights</span><span class="p">):</span>  <span class="c1"># pragma: no cover</span>
                 <span class="k">raise</span> <span class="n">MaxDiversificationNaNError</span><span class="p">(</span><span class="n">msgc</span><span class="p">)</span>
 
             <span class="n">msgd</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;max_div weight strategy failed: negative weights detected&quot;</span>
-                <span class="sa">f</span><span class="s2">&quot; - weights: </span><span class="si">{</span><span class="p">[</span><span class="nb">round</span><span class="p">(</span><span class="n">w</span><span class="p">,</span><span class="w"> </span><span class="mi">6</span><span class="p">)</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">w</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">weights</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="s2">"max_div weight strategy failed: negative weights detected"</span>
+                <span class="sa">f</span><span class="s2">" - weights: </span><span class="si">{</span><span class="p">[</span><span class="nb">round</span><span class="p">(</span><span class="n">w</span><span class="p">,</span><span class="w"> </span><span class="mi">6</span><span class="p">)</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">w</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">weights</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span>
             <span class="p">)</span>
             <span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">weight</span> <span class="o">&lt;</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">weight</span> <span class="ow">in</span> <span class="n">weights</span><span class="p">):</span>
                 <span class="k">raise</span> <span class="n">MaxDiversificationNegativeWeightsError</span><span class="p">(</span><span class="n">msgd</span><span class="p">)</span>
 
         <span class="k">except</span> <span class="n">linalg</span><span class="o">.</span><span class="n">LinAlgError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
             <span class="n">msge</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;max_div weight strategy failed: &quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;correlation matrix is singular - </span><span class="si">{</span><span class="n">e</span><span class="si">!s}</span><span class="s2">&quot;</span>
+                <span class="s2">"max_div weight strategy failed: "</span>
+                <span class="sa">f</span><span class="s2">"correlation matrix is singular - </span><span class="si">{</span><span class="n">e</span><span class="si">!s}</span><span class="s2">"</span>
             <span class="p">)</span>
             <span class="k">raise</span> <span class="n">MaxDiversificationNaNError</span><span class="p">(</span><span class="n">msge</span><span class="p">)</span> <span class="kn">from</span><span class="w"> </span><span class="nn">e</span>
         <span class="k">else</span><span class="p">:</span>
@@ -1495,14 +1495,14 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">returns</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate minimum volatility overweight weights.</span>
+<span class="w">        </span><span class="sd">"""Calculate minimum volatility overweight weights.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            returns: Returns DataFrame.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            List of minimum volatility overweight weights.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">vols</span> <span class="o">=</span> <span class="n">std</span><span class="p">(</span><span class="n">returns</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
         <span class="n">min_vol_idx</span> <span class="o">=</span> <span class="n">vols</span><span class="o">.</span><span class="n">argmin</span><span class="p">()</span>
         <span class="n">min_vol_weight</span> <span class="o">=</span> <span class="mf">0.6</span>
@@ -1516,7 +1516,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">weight_strat</span><span class="p">:</span> <span class="n">LiteralPortfolioWeightings</span><span class="p">,</span>
         <span class="n">returns</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate weights based on strategy.</span>
+<span class="w">        </span><span class="sd">"""Calculate weights based on strategy.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            weight_strat: Weight calculation strategy.</span>
@@ -1527,17 +1527,17 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            NotImplementedError: If strategy is not implemented.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">&quot;eq_weights&quot;</span><span class="p">:</span>
+<span class="sd">        """</span>
+        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">"eq_weights"</span><span class="p">:</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_eq_weights</span><span class="p">()</span>
-        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">&quot;inv_vol&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">"inv_vol"</span><span class="p">:</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_inv_vol_weights</span><span class="p">(</span><span class="n">returns</span><span class="p">)</span>
-        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">&quot;max_div&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">"max_div"</span><span class="p">:</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_max_div_weights</span><span class="p">(</span><span class="n">returns</span><span class="p">)</span>
-        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">&quot;min_vol_overweight&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">weight_strat</span> <span class="o">==</span> <span class="s2">"min_vol_overweight"</span><span class="p">:</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_calculate_min_vol_overweight_weights</span><span class="p">(</span><span class="n">returns</span><span class="p">)</span>
 
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Weight strategy not implemented&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Weight strategy not implemented"</span>
         <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
 <div class="viewcode-block" id="OpenFrame.make_portfolio">
@@ -1547,7 +1547,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
         <span class="n">weight_strat</span><span class="p">:</span> <span class="n">LiteralPortfolioWeightings</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate a basket timeseries based on the supplied weights.</span>
+<span class="w">        </span><span class="sd">"""Calculate a basket timeseries based on the supplied weights.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            name: Name of the basket timeseries.</span>
@@ -1555,11 +1555,11 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            A basket timeseries.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">weights</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">weight_strat</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;OpenFrame weights property must be provided &quot;</span>
-                <span class="s2">&quot;to run the make_portfolio method.&quot;</span>
+                <span class="s2">"OpenFrame weights property must be provided "</span>
+                <span class="s2">"to run the make_portfolio method."</span>
             <span class="p">)</span>
             <span class="k">raise</span> <span class="n">NoWeightsError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -1575,7 +1575,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="p">(</span><span class="n">returns</span> <span class="o">@</span> <span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">))</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span><span class="o">.</span><span class="n">cumprod</span><span class="p">(),</span>
             <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
             <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="n">name</span><span class="p">],</span> <span class="p">[</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">]],</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -1588,7 +1588,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">observations</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">21</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate rolling Information Ratio.</span>
+<span class="w">        </span><span class="sd">"""Calculate rolling Information Ratio.</span>
 
 <span class="sd">        The Information Ratio equals ( fund return less index return ) divided by</span>
 <span class="sd">        the Tracking Error. And the Tracking Error is the standard deviation of the</span>
@@ -1606,16 +1606,16 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Rolling Information Ratios.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">long_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span>
+            <span class="s2">"tuple[str, str]"</span><span class="p">,</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">long_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">,</span>
         <span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="n">short_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span>
+            <span class="s2">"tuple[str, str]"</span><span class="p">,</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">short_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">,</span>
         <span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-        <span class="n">ratio_label</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">long_label</span><span class="si">}</span><span class="s2"> / </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">&quot;</span>
+        <span class="n">ratio_label</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">long_label</span><span class="si">}</span><span class="s2"> / </span><span class="si">{</span><span class="n">short_label</span><span class="si">}</span><span class="s2">"</span>
         <span class="k">if</span> <span class="n">periods_in_a_year_fixed</span><span class="p">:</span>
             <span class="n">time_factor</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">periods_in_a_year_fixed</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
@@ -1640,7 +1640,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">voldf</span> <span class="o">=</span> <span class="n">voldf</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span>
 
         <span class="n">ratiodf</span> <span class="o">=</span> <span class="p">(</span><span class="n">retdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="n">voldf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span>
-        <span class="n">ratiodf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[[</span><span class="n">ratio_label</span><span class="p">],</span> <span class="p">[</span><span class="s2">&quot;Information Ratio&quot;</span><span class="p">]]</span>
+        <span class="n">ratiodf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="p">[[</span><span class="n">ratio_label</span><span class="p">],</span> <span class="p">[</span><span class="s2">"Information Ratio"</span><span class="p">]]</span>
 
         <span class="k">return</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">ratiodf</span><span class="p">)</span></div>
 
@@ -1654,7 +1654,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">observations</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">21</span><span class="p">,</span>
         <span class="n">dlta_degr_freedms</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate rolling Market Beta.</span>
+<span class="w">        </span><span class="sd">"""Calculate rolling Market Beta.</span>
 
 <span class="sd">        Calculates Beta as Co-variance of asset &amp; market divided by Variance</span>
 <span class="sd">        of the market.</span>
@@ -1671,12 +1671,12 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Rolling Betas.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">market_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">market_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span>
+<span class="sd">        """</span>
+        <span class="n">market_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">market_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span>
             <span class="mi">0</span>
         <span class="p">]</span>
-        <span class="n">asset_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">asset_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-        <span class="n">beta_label</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset_label</span><span class="si">}</span><span class="s2"> / </span><span class="si">{</span><span class="n">market_label</span><span class="si">}</span><span class="s2">&quot;</span>
+        <span class="n">asset_label</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">asset_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+        <span class="n">beta_label</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset_label</span><span class="si">}</span><span class="s2"> / </span><span class="si">{</span><span class="n">market_label</span><span class="si">}</span><span class="s2">"</span>
 
         <span class="n">rolling</span> <span class="o">=</span> <span class="p">(</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span>
@@ -1702,7 +1702,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="p">)</span>
         <span class="n">rollbeta</span> <span class="o">=</span> <span class="n">rollbetaseries</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span>
         <span class="n">rollbeta</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">rollbeta</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-        <span class="n">rollbeta</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">([[</span><span class="n">beta_label</span><span class="p">],</span> <span class="p">[</span><span class="s2">&quot;Beta&quot;</span><span class="p">]])</span>
+        <span class="n">rollbeta</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">([[</span><span class="n">beta_label</span><span class="p">],</span> <span class="p">[</span><span class="s2">"Beta"</span><span class="p">]])</span>
 
         <span class="k">return</span> <span class="n">rollbeta</span></div>
 
@@ -1715,7 +1715,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">second_column</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
         <span class="n">observations</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">21</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate rolling Correlation.</span>
+<span class="w">        </span><span class="sd">"""Calculate rolling Correlation.</span>
 
 <span class="sd">        Calculates correlation between two series. The period with</span>
 <span class="sd">        at least the given number of observations is the first period calculated.</span>
@@ -1730,11 +1730,11 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Rolling Correlations.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">corr_label</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-            <span class="o">+</span> <span class="s2">&quot;_VS_&quot;</span>
-            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, str]&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="o">+</span> <span class="s2">"_VS_"</span>
+            <span class="o">+</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, str]"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">second_column</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
         <span class="p">)</span>
         <span class="n">first_series</span> <span class="o">=</span> <span class="p">(</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">first_column</span><span class="p">]</span>
@@ -1747,7 +1747,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">corrdf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
             <span class="p">[</span>
                 <span class="p">[</span><span class="n">corr_label</span><span class="p">],</span>
-                <span class="p">[</span><span class="s2">&quot;Rolling correlation&quot;</span><span class="p">],</span>
+                <span class="p">[</span><span class="s2">"Rolling correlation"</span><span class="p">],</span>
             <span class="p">],</span>
         <span class="p">)</span>
 
@@ -1760,7 +1760,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">dependent_column</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">ValueType</span><span class="p">],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">OpenTimeSeries</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform a multi-factor linear regression.</span>
+<span class="w">        </span><span class="sd">"""Perform a multi-factor linear regression.</span>
 
 <span class="sd">        This function treats one specified column in the DataFrame as the dependent</span>
 <span class="sd">        variable (y) and uses all remaining columns as independent variables (X).</span>
@@ -1780,28 +1780,28 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <span class="sd">        Raises:</span>
 <span class="sd">            KeyError: If the column tuple is not found in the OpenFrame.tsdf.columns.</span>
 <span class="sd">            ValueError: If not all series are returnseries (ValueType.RTRN).</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">key_msg</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="sa">f</span><span class="s2">&quot;Tuple (</span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">, &quot;</span>
-            <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2">) not found in data.&quot;</span>
+            <span class="sa">f</span><span class="s2">"Tuple (</span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">, "</span>
+            <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2">) not found in data."</span>
         <span class="p">)</span>
         <span class="k">if</span> <span class="n">dependent_column</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">KeyError</span><span class="p">(</span><span class="n">key_msg</span><span class="p">)</span>
 
-        <span class="n">vtype_msg</span> <span class="o">=</span> <span class="s2">&quot;All series should be of ValueType.RTRN.&quot;</span>
+        <span class="n">vtype_msg</span> <span class="o">=</span> <span class="s2">"All series should be of ValueType.RTRN."</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">all</span><span class="p">(</span><span class="n">x</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)):</span>
             <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">vtype_msg</span><span class="p">)</span>
 
         <span class="n">dependent</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[</span><span class="n">dependent_column</span><span class="p">]</span>
         <span class="n">factors</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="n">dependent_column</span><span class="p">])</span>
-        <span class="n">indx</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;R-square&quot;</span><span class="p">,</span> <span class="s2">&quot;Intercept&quot;</span><span class="p">,</span> <span class="o">*</span><span class="n">factors</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span>
+        <span class="n">indx</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"R-square"</span><span class="p">,</span> <span class="s2">"Intercept"</span><span class="p">,</span> <span class="o">*</span><span class="n">factors</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)]</span>
 
         <span class="n">model</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
         <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">factors</span><span class="p">,</span> <span class="n">dependent</span><span class="p">)</span>
 
         <span class="n">predictions</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;Predicted </span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="n">date</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">date</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">],</span>
+            <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"Predicted </span><span class="si">{</span><span class="n">dependent_column</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="n">date</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">date</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">],</span>
             <span class="n">values</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">factors</span><span class="p">)),</span>
             <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">,</span>
         <span class="p">)</span>
@@ -1820,7 +1820,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">equal_weights</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Validate and prepare inputs for rebalanced portfolio.</span>
+<span class="w">        </span><span class="sd">"""Validate and prepare inputs for rebalanced portfolio.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            items: List of items to include. If None, uses all items.</span>
@@ -1834,30 +1834,30 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <span class="sd">            WeightsNotProvidedError: If weights are required but not provided.</span>
 <span class="sd">            TypeError: If items is not a list.</span>
 <span class="sd">            PortfolioItemsNotWithinFrameError: If items are invalid.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="n">bal_weights</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">equal_weights</span><span class="p">:</span>
             <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">weights</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Weights must be provided.&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Weights must be provided."</span>
                 <span class="k">raise</span> <span class="n">WeightsNotProvidedError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
             <span class="n">bal_weights</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">)</span>
 
         <span class="k">if</span> <span class="n">items</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">items</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Items must be passed as list.&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Items must be passed as list."</span>
             <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">items</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
                 <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
             <span class="k">if</span> <span class="ow">not</span> <span class="n">items</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Items for portfolio must be within SeriesFrame items.&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Items for portfolio must be within SeriesFrame items."</span>
                 <span class="k">raise</span> <span class="n">PortfolioItemsNotWithinFrameError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
             <span class="k">if</span> <span class="ow">not</span> <span class="nb">set</span><span class="p">(</span><span class="n">items</span><span class="p">)</span> <span class="o">&lt;=</span> <span class="nb">set</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">):</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Items for portfolio must be within SeriesFrame items.&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Items for portfolio must be within SeriesFrame items."</span>
                 <span class="k">raise</span> <span class="n">PortfolioItemsNotWithinFrameError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
         <span class="k">if</span> <span class="n">equal_weights</span><span class="p">:</span>
             <span class="n">bal_weights</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">items</span><span class="p">)]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">items</span><span class="p">)</span>
 
-        <span class="k">return</span> <span class="n">items</span><span class="p">,</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;list[float]&quot;</span><span class="p">,</span> <span class="n">bal_weights</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">items</span><span class="p">,</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"list[float]"</span><span class="p">,</span> <span class="n">bal_weights</span><span class="p">)</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_initialize_rebalance_output</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
@@ -1865,7 +1865,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
         <span class="n">cash_values</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Initialize output structure for rebalanced portfolio.</span>
+<span class="w">        </span><span class="sd">"""Initialize output structure for rebalanced portfolio.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            items: List of items in portfolio.</span>
@@ -1874,35 +1874,35 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Initialized output dictionary.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">output</span> <span class="o">=</span> <span class="p">{</span>
             <span class="n">item</span><span class="p">:</span> <span class="p">{</span>
                 <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">:</span> <span class="p">[],</span>
-                <span class="s2">&quot;buysell_qty&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                <span class="s2">&quot;position&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                <span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                <span class="s2">&quot;twr&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                <span class="s2">&quot;settle&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                <span class="s2">"buysell_qty"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                <span class="s2">"position"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                <span class="s2">"value"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                <span class="s2">"twr"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                <span class="s2">"settle"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
             <span class="p">}</span>
             <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">items</span>
         <span class="p">}</span>
         <span class="n">output</span><span class="o">.</span><span class="n">update</span><span class="p">(</span>
             <span class="p">{</span>
-                <span class="s2">&quot;cash&quot;</span><span class="p">:</span> <span class="p">{</span>
+                <span class="s2">"cash"</span><span class="p">:</span> <span class="p">{</span>
                     <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">:</span> <span class="n">cash_values</span><span class="p">,</span>
-                    <span class="s2">&quot;buysell_qty&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                    <span class="s2">&quot;position&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                    <span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                    <span class="s2">&quot;twr&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
-                    <span class="s2">&quot;settle&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                    <span class="s2">"buysell_qty"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                    <span class="s2">"position"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                    <span class="s2">"value"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                    <span class="s2">"twr"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
+                    <span class="s2">"settle"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span><span class="p">,</span>
                 <span class="p">},</span>
                 <span class="n">name</span><span class="p">:</span> <span class="p">{</span>
                     <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
-                    <span class="s2">&quot;buysell_qty&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
-                    <span class="s2">&quot;position&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
-                    <span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
-                    <span class="s2">&quot;twr&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
-                    <span class="s2">&quot;settle&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                    <span class="s2">"buysell_qty"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                    <span class="s2">"position"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                    <span class="s2">"value"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                    <span class="s2">"twr"</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                    <span class="s2">"settle"</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
                 <span class="p">},</span>
             <span class="p">},</span>
         <span class="p">)</span>
@@ -1915,38 +1915,38 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">output</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]],</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Initialize positions for the first day.</span>
+<span class="w">        </span><span class="sd">"""Initialize positions for the first day.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            items: List of items in portfolio.</span>
 <span class="sd">            bal_weights: Weights for each item.</span>
 <span class="sd">            output: Output dictionary to update.</span>
 <span class="sd">            name: Name of the portfolio.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">for</span> <span class="n">item</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">items</span><span class="p">,</span> <span class="n">bal_weights</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
             <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;list[float]&quot;</span><span class="p">,</span>
+                <span class="s2">"list[float]"</span><span class="p">,</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[(</span><span class="n">item</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">)]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
                 <span class="n">weight</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="p">[(</span><span class="n">item</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">)]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">/</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
             <span class="p">)</span>
 
-        <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
         <span class="p">)</span>
-        <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_process_rebalancing_day</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
@@ -1956,7 +1956,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">output</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]],</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Process a rebalancing day.</span>
+<span class="w">        </span><span class="sd">"""Process a rebalancing day.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            day: Current day index.</span>
@@ -1967,31 +1967,31 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Tuple of (portfolio_value, settle_value).</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">portfolio_value</span> <span class="o">=</span> <span class="mf">0.0</span>
         <span class="n">settle_value</span> <span class="o">=</span> <span class="mf">0.0</span>
 
         <span class="k">for</span> <span class="n">item</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">items</span><span class="p">,</span> <span class="n">bal_weights</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
                 <span class="n">weight</span>
-                <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">/</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+                <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">/</span> <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
             <span class="p">)</span> <span class="o">/</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">portfolio_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-                <span class="o">/</span> <span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">])</span>
-                <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="n">portfolio_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+                <span class="o">/</span> <span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="n">day</span><span class="p">])</span>
+                <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="o">-</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">settle_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">settle_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
 
         <span class="k">return</span> <span class="n">portfolio_value</span><span class="p">,</span> <span class="n">settle_value</span>
 
@@ -2001,7 +2001,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">items</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
         <span class="n">output</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Process a non-rebalancing day.</span>
+<span class="w">        </span><span class="sd">"""Process a non-rebalancing day.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            day: Current day index.</span>
@@ -2010,19 +2010,19 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Portfolio value.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">portfolio_value</span> <span class="o">=</span> <span class="mf">0.0</span>
 
         <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">items</span><span class="p">:</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
             <span class="p">)</span>
-            <span class="n">portfolio_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-                <span class="o">/</span> <span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;settle&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">])</span>
-                <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="n">portfolio_value</span> <span class="o">+=</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+                <span class="o">/</span> <span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"settle"</span><span class="p">][</span><span class="n">day</span><span class="p">])</span>
+                <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="n">item</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
             <span class="p">)</span>
 
         <span class="k">return</span> <span class="n">portfolio_value</span>
@@ -2035,7 +2035,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">output</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]],</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Update cash and portfolio values for a day.</span>
+<span class="w">        </span><span class="sd">"""Update cash and portfolio values for a day.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            day: Current day index.</span>
@@ -2043,22 +2043,22 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 <span class="sd">            settle_value: Total settle value.</span>
 <span class="sd">            output: Output dictionary to update.</span>
 <span class="sd">            name: Name of the portfolio.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">settle_value</span>
-        <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
-            <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-            <span class="o">/</span> <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
-            <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;buysell_qty&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+<span class="sd">        """</span>
+        <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">settle_value</span>
+        <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="o">*</span> <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+            <span class="o">/</span> <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"buysell_qty"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
         <span class="p">)</span>
-        <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-        <span class="n">total_portfolio_value</span> <span class="o">=</span> <span class="n">portfolio_value</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="s2">&quot;cash&quot;</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
-        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
-        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">total_portfolio_value</span>
-        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;value&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">/</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;position&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+        <span class="n">total_portfolio_value</span> <span class="o">=</span> <span class="n">portfolio_value</span> <span class="o">+</span> <span class="n">output</span><span class="p">[</span><span class="s2">"cash"</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">total_portfolio_value</span>
+        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"value"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">/</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"position"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
         <span class="p">)</span>
-        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">&quot;twr&quot;</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
+        <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">][</span><span class="n">day</span><span class="p">]</span> <span class="o">=</span> <span class="n">output</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s2">"twr"</span><span class="p">][</span><span class="n">day</span><span class="p">]</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_build_rebalance_result</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
@@ -2066,7 +2066,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">instruments</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
         <span class="n">subheaders</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span> <span class="o">|</span> <span class="n">ValueType</span><span class="p">],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Build result DataFrame from output dictionary.</span>
+<span class="w">        </span><span class="sd">"""Build result DataFrame from output dictionary.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            output: Output dictionary with all calculated values.</span>
@@ -2075,7 +2075,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            DataFrame with MultiIndex columns.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">result</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">()</span>
         <span class="k">for</span> <span class="n">outvalue</span> <span class="ow">in</span> <span class="n">output</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
             <span class="n">result</span> <span class="o">=</span> <span class="n">concat</span><span class="p">(</span>
@@ -2083,7 +2083,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                     <span class="n">result</span><span class="p">,</span>
                     <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">outvalue</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">),</span>
                 <span class="p">],</span>
-                <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span>
+                <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span>
             <span class="p">)</span>
         <span class="n">lvlone</span><span class="p">,</span> <span class="n">lvltwo</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
         <span class="k">for</span> <span class="n">instr</span> <span class="ow">in</span> <span class="n">instruments</span><span class="p">:</span>
@@ -2105,7 +2105,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="n">equal_weights</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">drop_extras</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">OpenFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a rebalanced portfolio from the OpenFrame constituents.</span>
+<span class="w">        </span><span class="sd">"""Create a rebalanced portfolio from the OpenFrame constituents.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            name: Name of the portfolio.</span>
@@ -2121,7 +2121,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            OpenFrame containing the rebalanced portfolio.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">items</span><span class="p">,</span> <span class="n">bal_weights</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_validate_and_prepare_rebalance_inputs</span><span class="p">(</span>
             <span class="n">items</span><span class="p">,</span>
             <span class="n">bal_weights</span><span class="p">,</span>
@@ -2131,7 +2131,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">cash_index</span><span class="p">:</span>
             <span class="n">cash_index</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">cash_index</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">reindex</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
             <span class="n">cash_values</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;list[float]&quot;</span><span class="p">,</span> <span class="n">cash_index</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
+                <span class="s2">"list[float]"</span><span class="p">,</span> <span class="n">cash_index</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
             <span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="n">cash_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">1.0</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">length</span>
@@ -2141,18 +2141,18 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
 
         <span class="n">ccies</span> <span class="o">=</span> <span class="nb">list</span><span class="p">({</span><span class="n">serie</span><span class="o">.</span><span class="n">currency</span> <span class="k">for</span> <span class="n">serie</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">constituents</span><span class="p">})</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ccies</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Items for portfolio must be denominated in same currency.&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Items for portfolio must be denominated in same currency."</span>
             <span class="k">raise</span> <span class="n">MultipleCurrenciesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="n">currency</span> <span class="o">=</span> <span class="n">ccies</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
-        <span class="n">instruments</span> <span class="o">=</span> <span class="p">[</span><span class="o">*</span><span class="n">items</span><span class="p">,</span> <span class="s2">&quot;cash&quot;</span><span class="p">,</span> <span class="n">name</span><span class="p">]</span>
+        <span class="n">instruments</span> <span class="o">=</span> <span class="p">[</span><span class="o">*</span><span class="n">items</span><span class="p">,</span> <span class="s2">"cash"</span><span class="p">,</span> <span class="n">name</span><span class="p">]</span>
         <span class="n">subheaders</span> <span class="o">=</span> <span class="p">[</span>
             <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
-            <span class="s2">&quot;buysell_qty&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;position&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;value&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;twr&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;settle&quot;</span><span class="p">,</span>
+            <span class="s2">"buysell_qty"</span><span class="p">,</span>
+            <span class="s2">"position"</span><span class="p">,</span>
+            <span class="s2">"value"</span><span class="p">,</span>
+            <span class="s2">"twr"</span><span class="p">,</span>
+            <span class="s2">"settle"</span><span class="p">,</span>
         <span class="p">]</span>
 
         <span class="n">output</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rebalance_output</span><span class="p">(</span>
@@ -2209,7 +2209,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="n">series</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span>
                 <span class="p">[</span>
                     <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-                        <span class="n">dframe</span><span class="o">=</span><span class="n">result</span><span class="p">[(</span><span class="n">item</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="s2">&quot;twr&quot;</span><span class="p">)],</span>
+                        <span class="n">dframe</span><span class="o">=</span><span class="n">result</span><span class="p">[(</span><span class="n">item</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="s2">"twr"</span><span class="p">)],</span>
                         <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
                         <span class="n">baseccy</span><span class="o">=</span><span class="n">item</span><span class="o">.</span><span class="n">currency</span><span class="p">,</span>
                         <span class="n">local_ccy</span><span class="o">=</span><span class="n">item</span><span class="o">.</span><span class="n">local_ccy</span><span class="p">,</span>
@@ -2219,7 +2219,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
             <span class="p">)</span>
             <span class="n">series</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
                 <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-                    <span class="n">dframe</span><span class="o">=</span><span class="n">result</span><span class="p">[(</span><span class="n">name</span><span class="p">,</span> <span class="s2">&quot;twr&quot;</span><span class="p">)],</span>
+                    <span class="n">dframe</span><span class="o">=</span><span class="n">result</span><span class="p">[(</span><span class="n">name</span><span class="p">,</span> <span class="s2">"twr"</span><span class="p">)],</span>
                     <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
                     <span class="n">baseccy</span><span class="o">=</span><span class="n">currency</span><span class="p">,</span>
                     <span class="n">local_ccy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
@@ -2233,7 +2233,7 @@ <h1>Source code for openseries.frame</h1><div class="highlight"><pre>
                         <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
                         <span class="n">baseccy</span><span class="o">=</span><span class="n">currency</span><span class="p">,</span>
                         <span class="n">local_ccy</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-                    <span class="p">)</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">col</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">col</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">!s}</span><span class="s2">&quot;</span><span class="p">)</span>
+                    <span class="p">)</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">col</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">col</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">!s}</span><span class="s2">"</span><span class="p">)</span>
                     <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">result</span><span class="o">.</span><span class="n">columns</span>
                 <span class="p">]</span>
             <span class="p">)</span>
diff --git a/docs/build/html/_modules/openseries/load_plotly.html b/docs/build/html/_modules/openseries/load_plotly.html
index 0b948bf6..ebab9690 100644
--- a/docs/build/html/_modules/openseries/load_plotly.html
+++ b/docs/build/html/_modules/openseries/load_plotly.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.load_plotly</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;Function to load plotly layout and configuration from local json file.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""Function to load plotly layout and configuration from local json file."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -125,18 +125,18 @@ <h1>Source code for openseries.load_plotly</h1><div class="highlight"><pre>
 
 <span class="n">logger</span> <span class="o">=</span> <span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;load_plotly_dict&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"load_plotly_dict"</span><span class="p">]</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_check_remote_file_existence</span><span class="p">(</span><span class="n">url</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Check if remote file exists.</span>
+<span class="w">    </span><span class="sd">"""Check if remote file exists.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        url: Path to remote file.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        True if url is valid and False otherwise.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">ok_code</span> <span class="o">=</span> <span class="mi">200</span>
 
     <span class="k">try</span><span class="p">:</span>
@@ -154,7 +154,7 @@ <h1>Source code for openseries.load_plotly</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">responsive</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">PlotlyLayoutType</span><span class="p">,</span> <span class="n">CaptorLogoType</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Load Plotly defaults.</span>
+<span class="w">    </span><span class="sd">"""Load Plotly defaults.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        responsive: Flag whether to load as responsive. Defaults to True.</span>
@@ -164,22 +164,22 @@ <h1>Source code for openseries.load_plotly</h1><div class="highlight"><pre>
 <span class="sd">        where config_and_layout is the Plotly config and layout template dict,</span>
 <span class="sd">        and logo is the Captor logo dict (may be empty if the remote logo is</span>
 <span class="sd">        unavailable).</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">package_dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="vm">__file__</span><span class="p">)</span><span class="o">.</span><span class="n">parent</span>
-    <span class="n">layoutfile</span> <span class="o">=</span> <span class="n">package_dir</span> <span class="o">/</span> <span class="s2">&quot;plotly_layouts.json&quot;</span>
-    <span class="n">logofile</span> <span class="o">=</span> <span class="n">package_dir</span> <span class="o">/</span> <span class="s2">&quot;plotly_captor_logo.json&quot;</span>
+    <span class="n">layoutfile</span> <span class="o">=</span> <span class="n">package_dir</span> <span class="o">/</span> <span class="s2">"plotly_layouts.json"</span>
+    <span class="n">logofile</span> <span class="o">=</span> <span class="n">package_dir</span> <span class="o">/</span> <span class="s2">"plotly_captor_logo.json"</span>
 
-    <span class="k">with</span> <span class="n">layoutfile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">&quot;r&quot;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">layout_file</span><span class="p">:</span>
+    <span class="k">with</span> <span class="n">layoutfile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">"r"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">layout_file</span><span class="p">:</span>
         <span class="n">fig</span> <span class="o">=</span> <span class="n">load</span><span class="p">(</span><span class="n">layout_file</span><span class="p">)</span>
-    <span class="k">with</span> <span class="n">logofile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">&quot;r&quot;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">logo_file</span><span class="p">:</span>
+    <span class="k">with</span> <span class="n">logofile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">"r"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">logo_file</span><span class="p">:</span>
         <span class="n">logo</span> <span class="o">=</span> <span class="n">load</span><span class="p">(</span><span class="n">logo_file</span><span class="p">)</span>
 
-    <span class="k">if</span> <span class="ow">not</span> <span class="n">_check_remote_file_existence</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="n">logo</span><span class="p">[</span><span class="s2">&quot;source&quot;</span><span class="p">]):</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Failed to add logo image from URL </span><span class="si">{</span><span class="n">logo</span><span class="p">[</span><span class="s1">&#39;source&#39;</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="n">_check_remote_file_existence</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="n">logo</span><span class="p">[</span><span class="s2">"source"</span><span class="p">]):</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Failed to add logo image from URL </span><span class="si">{</span><span class="n">logo</span><span class="p">[</span><span class="s1">'source'</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span>
         <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="n">logo</span> <span class="o">=</span> <span class="p">{}</span>
 
-    <span class="n">fig</span><span class="p">[</span><span class="s2">&quot;config&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s2">&quot;responsive&quot;</span><span class="p">:</span> <span class="n">responsive</span><span class="p">})</span>
+    <span class="n">fig</span><span class="p">[</span><span class="s2">"config"</span><span class="p">]</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s2">"responsive"</span><span class="p">:</span> <span class="n">responsive</span><span class="p">})</span>
 
     <span class="k">return</span> <span class="n">fig</span><span class="p">,</span> <span class="n">logo</span></div>
 
diff --git a/docs/build/html/_modules/openseries/owntypes.html b/docs/build/html/_modules/openseries/owntypes.html
index b2b0cc33..592963dc 100644
--- a/docs/build/html/_modules/openseries/owntypes.html
+++ b/docs/build/html/_modules/openseries/owntypes.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;Declaring types used throughout the project.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""Declaring types used throughout the project."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -137,17 +137,17 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <span class="k">else</span><span class="p">:</span>
     <span class="n">SeriesFloat</span> <span class="o">=</span> <span class="n">Series</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;ValueType&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"ValueType"</span><span class="p">]</span>
 
 
-<span class="n">SeriesOrFloat_co</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">&quot;SeriesOrFloat_co&quot;</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="n">SeriesFloat</span><span class="p">,</span> <span class="n">covariant</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">SeriesOrFloat_co</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"SeriesOrFloat_co"</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="n">SeriesFloat</span><span class="p">,</span> <span class="n">covariant</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 
 <span class="n">CountryStringType</span> <span class="o">=</span> <span class="n">Annotated</span><span class="p">[</span>
     <span class="nb">str</span><span class="p">,</span>
     <span class="n">StringConstraints</span><span class="p">(</span>
         <span class="n">strip_whitespace</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">&quot;^[A-Z]</span><span class="si">{2}</span><span class="s2">$&quot;</span><span class="p">,</span>
+        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">"^[A-Z]</span><span class="si">{2}</span><span class="s2">$"</span><span class="p">,</span>
         <span class="n">to_upper</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
         <span class="n">min_length</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
         <span class="n">max_length</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
@@ -161,7 +161,7 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="Countries">
 <a class="viewcode-back" href="../../api/types.html#openseries.Countries">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">Countries</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Declare Countries.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Declare Countries."""</span>
 
     <span class="n">countryinput</span><span class="p">:</span> <span class="n">CountriesType</span></div>
 
@@ -170,7 +170,7 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="n">Annotated</span><span class="p">[</span>
     <span class="nb">str</span><span class="p">,</span>
     <span class="n">StringConstraints</span><span class="p">(</span>
-        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">&quot;^[A-Z]</span><span class="si">{3}</span><span class="s2">$&quot;</span><span class="p">,</span>
+        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">"^[A-Z]</span><span class="si">{3}</span><span class="s2">$"</span><span class="p">,</span>
         <span class="n">to_upper</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
         <span class="n">min_length</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
         <span class="n">max_length</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
@@ -183,7 +183,7 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="Currency">
 <a class="viewcode-back" href="../../api/types.html#openseries.Currency">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">Currency</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Declare Currency.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Declare Currency."""</span>
 
     <span class="n">ccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span></div>
 
@@ -192,7 +192,7 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <span class="n">DateStringType</span> <span class="o">=</span> <span class="n">Annotated</span><span class="p">[</span>
     <span class="nb">str</span><span class="p">,</span>
     <span class="n">StringConstraints</span><span class="p">(</span>
-        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">&quot;^\d</span><span class="si">{4}</span><span class="s2">-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$&quot;</span><span class="p">,</span>
+        <span class="n">pattern</span><span class="o">=</span><span class="sa">r</span><span class="s2">"^\d</span><span class="si">{4}</span><span class="s2">-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$"</span><span class="p">,</span>
         <span class="n">strip_whitespace</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
         <span class="n">strict</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
         <span class="n">min_length</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
@@ -220,153 +220,153 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 
 <span class="n">CaptorLogoType</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span> <span class="o">|</span> <span class="nb">float</span><span class="p">]</span>
 
-<span class="n">LiteralJsonOutput</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;values&quot;</span><span class="p">,</span> <span class="s2">&quot;tsdf&quot;</span><span class="p">]</span>
-<span class="n">LiteralTrunc</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;before&quot;</span><span class="p">,</span> <span class="s2">&quot;after&quot;</span><span class="p">,</span> <span class="s2">&quot;both&quot;</span><span class="p">]</span>
+<span class="n">LiteralJsonOutput</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"values"</span><span class="p">,</span> <span class="s2">"tsdf"</span><span class="p">]</span>
+<span class="n">LiteralTrunc</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"before"</span><span class="p">,</span> <span class="s2">"after"</span><span class="p">,</span> <span class="s2">"both"</span><span class="p">]</span>
 <span class="n">LiteralLinePlotMode</span> <span class="o">=</span> <span class="p">(</span>
     <span class="n">Literal</span><span class="p">[</span>
-        <span class="s2">&quot;lines&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;markers&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;lines+markers&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;lines+text&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;markers+text&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;lines+markers+text&quot;</span><span class="p">,</span>
+        <span class="s2">"lines"</span><span class="p">,</span>
+        <span class="s2">"markers"</span><span class="p">,</span>
+        <span class="s2">"lines+markers"</span><span class="p">,</span>
+        <span class="s2">"lines+text"</span><span class="p">,</span>
+        <span class="s2">"markers+text"</span><span class="p">,</span>
+        <span class="s2">"lines+markers+text"</span><span class="p">,</span>
     <span class="p">]</span>
     <span class="o">|</span> <span class="kc">None</span>
 <span class="p">)</span>
-<span class="n">LiteralHowMerge</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;outer&quot;</span><span class="p">,</span> <span class="s2">&quot;inner&quot;</span><span class="p">]</span>
-<span class="n">LiteralQuantileInterp</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span> <span class="s2">&quot;lower&quot;</span><span class="p">,</span> <span class="s2">&quot;higher&quot;</span><span class="p">,</span> <span class="s2">&quot;midpoint&quot;</span><span class="p">,</span> <span class="s2">&quot;nearest&quot;</span><span class="p">]</span>
-<span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;B&quot;</span><span class="p">,</span> <span class="s2">&quot;BME&quot;</span><span class="p">,</span> <span class="s2">&quot;BQE&quot;</span><span class="p">,</span> <span class="s2">&quot;BYE&quot;</span><span class="p">]</span>
+<span class="n">LiteralHowMerge</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"outer"</span><span class="p">,</span> <span class="s2">"inner"</span><span class="p">]</span>
+<span class="n">LiteralQuantileInterp</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"linear"</span><span class="p">,</span> <span class="s2">"lower"</span><span class="p">,</span> <span class="s2">"higher"</span><span class="p">,</span> <span class="s2">"midpoint"</span><span class="p">,</span> <span class="s2">"nearest"</span><span class="p">]</span>
+<span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"B"</span><span class="p">,</span> <span class="s2">"BME"</span><span class="p">,</span> <span class="s2">"BQE"</span><span class="p">,</span> <span class="s2">"BYE"</span><span class="p">]</span>
 <span class="n">LiteralPandasReindexMethod</span> <span class="o">=</span> <span class="p">(</span>
-    <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;pad&quot;</span><span class="p">,</span> <span class="s2">&quot;ffill&quot;</span><span class="p">,</span> <span class="s2">&quot;backfill&quot;</span><span class="p">,</span> <span class="s2">&quot;bfill&quot;</span><span class="p">,</span> <span class="s2">&quot;nearest&quot;</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span>
+    <span class="n">Literal</span><span class="p">[</span><span class="s2">"pad"</span><span class="p">,</span> <span class="s2">"ffill"</span><span class="p">,</span> <span class="s2">"backfill"</span><span class="p">,</span> <span class="s2">"bfill"</span><span class="p">,</span> <span class="s2">"nearest"</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span>
 <span class="p">)</span>
-<span class="n">LiteralNanMethod</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;fill&quot;</span><span class="p">,</span> <span class="s2">&quot;drop&quot;</span><span class="p">]</span>
-<span class="n">LiteralCaptureRatio</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;up&quot;</span><span class="p">,</span> <span class="s2">&quot;down&quot;</span><span class="p">,</span> <span class="s2">&quot;both&quot;</span><span class="p">]</span>
-<span class="n">LiteralBarPlotMode</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;stack&quot;</span><span class="p">,</span> <span class="s2">&quot;group&quot;</span><span class="p">,</span> <span class="s2">&quot;overlay&quot;</span><span class="p">,</span> <span class="s2">&quot;relative&quot;</span><span class="p">]</span>
-<span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;file&quot;</span><span class="p">,</span> <span class="s2">&quot;div&quot;</span><span class="p">]</span>
-<span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="kc">True</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="s2">&quot;cdn&quot;</span><span class="p">]</span>
-<span class="n">LiteralPlotlyHistogramPlotType</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;bars&quot;</span><span class="p">,</span> <span class="s2">&quot;lines&quot;</span><span class="p">]</span>
-<span class="n">LiteralPlotlyHistogramBarMode</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;stack&quot;</span><span class="p">,</span> <span class="s2">&quot;group&quot;</span><span class="p">,</span> <span class="s2">&quot;overlay&quot;</span><span class="p">,</span> <span class="s2">&quot;relative&quot;</span><span class="p">]</span>
-<span class="n">LiteralPlotlyHistogramCurveType</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;normal&quot;</span><span class="p">,</span> <span class="s2">&quot;kde&quot;</span><span class="p">]</span>
+<span class="n">LiteralNanMethod</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"fill"</span><span class="p">,</span> <span class="s2">"drop"</span><span class="p">]</span>
+<span class="n">LiteralCaptureRatio</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"up"</span><span class="p">,</span> <span class="s2">"down"</span><span class="p">,</span> <span class="s2">"both"</span><span class="p">]</span>
+<span class="n">LiteralBarPlotMode</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"stack"</span><span class="p">,</span> <span class="s2">"group"</span><span class="p">,</span> <span class="s2">"overlay"</span><span class="p">,</span> <span class="s2">"relative"</span><span class="p">]</span>
+<span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"file"</span><span class="p">,</span> <span class="s2">"div"</span><span class="p">]</span>
+<span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="kc">True</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="s2">"cdn"</span><span class="p">]</span>
+<span class="n">LiteralPlotlyHistogramPlotType</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"bars"</span><span class="p">,</span> <span class="s2">"lines"</span><span class="p">]</span>
+<span class="n">LiteralPlotlyHistogramBarMode</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"stack"</span><span class="p">,</span> <span class="s2">"group"</span><span class="p">,</span> <span class="s2">"overlay"</span><span class="p">,</span> <span class="s2">"relative"</span><span class="p">]</span>
+<span class="n">LiteralPlotlyHistogramCurveType</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">"normal"</span><span class="p">,</span> <span class="s2">"kde"</span><span class="p">]</span>
 <span class="n">LiteralPlotlyHistogramHistNorm</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
-    <span class="s2">&quot;percent&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;probability&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;density&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;probability density&quot;</span><span class="p">,</span>
+    <span class="s2">"percent"</span><span class="p">,</span>
+    <span class="s2">"probability"</span><span class="p">,</span>
+    <span class="s2">"density"</span><span class="p">,</span>
+    <span class="s2">"probability density"</span><span class="p">,</span>
 <span class="p">]</span>
 <span class="n">LiteralPortfolioWeightings</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
-    <span class="s2">&quot;eq_weights&quot;</span><span class="p">,</span> <span class="s2">&quot;inv_vol&quot;</span><span class="p">,</span> <span class="s2">&quot;max_div&quot;</span><span class="p">,</span> <span class="s2">&quot;min_vol_overweight&quot;</span>
+    <span class="s2">"eq_weights"</span><span class="p">,</span> <span class="s2">"inv_vol"</span><span class="p">,</span> <span class="s2">"max_div"</span><span class="p">,</span> <span class="s2">"min_vol_overweight"</span>
 <span class="p">]</span>
 <span class="n">LiteralMinimizeMethods</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
-    <span class="s2">&quot;SLSQP&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;Nelder-Mead&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;Powell&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;CG&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;BFGS&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;Newton-CG&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;L-BFGS-B&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;TNC&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;COBYLA&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;trust-constr&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;dogleg&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;trust-ncg&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;trust-exact&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;trust-krylov&quot;</span><span class="p">,</span>
+    <span class="s2">"SLSQP"</span><span class="p">,</span>
+    <span class="s2">"Nelder-Mead"</span><span class="p">,</span>
+    <span class="s2">"Powell"</span><span class="p">,</span>
+    <span class="s2">"CG"</span><span class="p">,</span>
+    <span class="s2">"BFGS"</span><span class="p">,</span>
+    <span class="s2">"Newton-CG"</span><span class="p">,</span>
+    <span class="s2">"L-BFGS-B"</span><span class="p">,</span>
+    <span class="s2">"TNC"</span><span class="p">,</span>
+    <span class="s2">"COBYLA"</span><span class="p">,</span>
+    <span class="s2">"trust-constr"</span><span class="p">,</span>
+    <span class="s2">"dogleg"</span><span class="p">,</span>
+    <span class="s2">"trust-ncg"</span><span class="p">,</span>
+    <span class="s2">"trust-exact"</span><span class="p">,</span>
+    <span class="s2">"trust-krylov"</span><span class="p">,</span>
 <span class="p">]</span>
 
 <span class="n">LiteralSeriesProps</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
-    <span class="s2">&quot;value_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;geo_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;arithmetic_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;vol&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;downside_deviation&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;ret_vol_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;sortino_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;kappa3_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;z_score&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;skew&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;kurtosis&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;positive_share&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;var_down&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;cvar_down&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;vol_from_var&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;worst&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;worst_month&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown_cal_year&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown_date&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;first_idx&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;last_idx&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;length&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;span_of_days&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;yearfrac&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;periods_in_a_year&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;autocorr&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;partial_autocorr&quot;</span><span class="p">,</span>
+    <span class="s2">"value_ret"</span><span class="p">,</span>
+    <span class="s2">"geo_ret"</span><span class="p">,</span>
+    <span class="s2">"arithmetic_ret"</span><span class="p">,</span>
+    <span class="s2">"vol"</span><span class="p">,</span>
+    <span class="s2">"downside_deviation"</span><span class="p">,</span>
+    <span class="s2">"ret_vol_ratio"</span><span class="p">,</span>
+    <span class="s2">"sortino_ratio"</span><span class="p">,</span>
+    <span class="s2">"kappa3_ratio"</span><span class="p">,</span>
+    <span class="s2">"z_score"</span><span class="p">,</span>
+    <span class="s2">"skew"</span><span class="p">,</span>
+    <span class="s2">"kurtosis"</span><span class="p">,</span>
+    <span class="s2">"positive_share"</span><span class="p">,</span>
+    <span class="s2">"var_down"</span><span class="p">,</span>
+    <span class="s2">"cvar_down"</span><span class="p">,</span>
+    <span class="s2">"vol_from_var"</span><span class="p">,</span>
+    <span class="s2">"worst"</span><span class="p">,</span>
+    <span class="s2">"worst_month"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown_cal_year"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown_date"</span><span class="p">,</span>
+    <span class="s2">"first_idx"</span><span class="p">,</span>
+    <span class="s2">"last_idx"</span><span class="p">,</span>
+    <span class="s2">"length"</span><span class="p">,</span>
+    <span class="s2">"span_of_days"</span><span class="p">,</span>
+    <span class="s2">"yearfrac"</span><span class="p">,</span>
+    <span class="s2">"periods_in_a_year"</span><span class="p">,</span>
+    <span class="s2">"autocorr"</span><span class="p">,</span>
+    <span class="s2">"partial_autocorr"</span><span class="p">,</span>
 <span class="p">]</span>
 <span class="n">LiteralFrameProps</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
-    <span class="s2">&quot;value_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;geo_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;arithmetic_ret&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;autocorr&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;vol&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;downside_deviation&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;ret_vol_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;sortino_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;kappa3_ratio&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;z_score&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;skew&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;kurtosis&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;positive_share&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;var_down&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;cvar_down&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;vol_from_var&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;worst&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;worst_month&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown_date&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;max_drawdown_cal_year&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;first_indices&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;last_indices&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;lengths_of_items&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;span_of_days_all&quot;</span><span class="p">,</span>
+    <span class="s2">"value_ret"</span><span class="p">,</span>
+    <span class="s2">"geo_ret"</span><span class="p">,</span>
+    <span class="s2">"arithmetic_ret"</span><span class="p">,</span>
+    <span class="s2">"autocorr"</span><span class="p">,</span>
+    <span class="s2">"vol"</span><span class="p">,</span>
+    <span class="s2">"downside_deviation"</span><span class="p">,</span>
+    <span class="s2">"ret_vol_ratio"</span><span class="p">,</span>
+    <span class="s2">"sortino_ratio"</span><span class="p">,</span>
+    <span class="s2">"kappa3_ratio"</span><span class="p">,</span>
+    <span class="s2">"z_score"</span><span class="p">,</span>
+    <span class="s2">"skew"</span><span class="p">,</span>
+    <span class="s2">"kurtosis"</span><span class="p">,</span>
+    <span class="s2">"positive_share"</span><span class="p">,</span>
+    <span class="s2">"var_down"</span><span class="p">,</span>
+    <span class="s2">"cvar_down"</span><span class="p">,</span>
+    <span class="s2">"vol_from_var"</span><span class="p">,</span>
+    <span class="s2">"worst"</span><span class="p">,</span>
+    <span class="s2">"worst_month"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown_date"</span><span class="p">,</span>
+    <span class="s2">"max_drawdown_cal_year"</span><span class="p">,</span>
+    <span class="s2">"first_indices"</span><span class="p">,</span>
+    <span class="s2">"last_indices"</span><span class="p">,</span>
+    <span class="s2">"lengths_of_items"</span><span class="p">,</span>
+    <span class="s2">"span_of_days_all"</span><span class="p">,</span>
 <span class="p">]</span>
 
 
 <div class="viewcode-block" id="PropertiesList">
 <a class="viewcode-back" href="../../api/types.html#openseries.PropertiesList">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">PropertiesList</span><span class="p">(</span><span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Base class for allowed property arguments definition.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Base class for allowed property arguments definition."""</span>
 
     <span class="n">allowed_strings</span><span class="p">:</span> <span class="n">ClassVar</span><span class="p">[</span><span class="nb">set</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="p">{</span>
-        <span class="s2">&quot;value_ret&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;geo_ret&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;arithmetic_ret&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;vol&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;downside_deviation&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;ret_vol_ratio&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;sortino_ratio&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;kappa3_ratio&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;omega_ratio&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;z_score&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;skew&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;kurtosis&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;positive_share&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;var_down&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;cvar_down&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;vol_from_var&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;worst&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;worst_month&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;max_drawdown&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;max_drawdown_date&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;max_drawdown_cal_year&quot;</span><span class="p">,</span>
+        <span class="s2">"value_ret"</span><span class="p">,</span>
+        <span class="s2">"geo_ret"</span><span class="p">,</span>
+        <span class="s2">"arithmetic_ret"</span><span class="p">,</span>
+        <span class="s2">"vol"</span><span class="p">,</span>
+        <span class="s2">"downside_deviation"</span><span class="p">,</span>
+        <span class="s2">"ret_vol_ratio"</span><span class="p">,</span>
+        <span class="s2">"sortino_ratio"</span><span class="p">,</span>
+        <span class="s2">"kappa3_ratio"</span><span class="p">,</span>
+        <span class="s2">"omega_ratio"</span><span class="p">,</span>
+        <span class="s2">"z_score"</span><span class="p">,</span>
+        <span class="s2">"skew"</span><span class="p">,</span>
+        <span class="s2">"kurtosis"</span><span class="p">,</span>
+        <span class="s2">"positive_share"</span><span class="p">,</span>
+        <span class="s2">"var_down"</span><span class="p">,</span>
+        <span class="s2">"cvar_down"</span><span class="p">,</span>
+        <span class="s2">"vol_from_var"</span><span class="p">,</span>
+        <span class="s2">"worst"</span><span class="p">,</span>
+        <span class="s2">"worst_month"</span><span class="p">,</span>
+        <span class="s2">"max_drawdown"</span><span class="p">,</span>
+        <span class="s2">"max_drawdown_date"</span><span class="p">,</span>
+        <span class="s2">"max_drawdown_cal_year"</span><span class="p">,</span>
     <span class="p">}</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_validate</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Validate the string input of the all_properties method.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Validate the string input of the all_properties method."""</span>
         <span class="n">seen</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
         <span class="n">invalids</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
         <span class="n">duplicates</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">""</span>
         <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="p">:</span>
             <span class="k">if</span> <span class="n">item</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">allowed_strings</span><span class="p">:</span>
                 <span class="n">invalids</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
@@ -375,11 +375,11 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
             <span class="n">seen</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">invalids</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">+=</span> <span class="p">(</span>
-                <span class="sa">f</span><span class="s2">&quot;Invalid string(s): </span><span class="si">{</span><span class="nb">list</span><span class="p">(</span><span class="n">invalids</span><span class="p">)</span><span class="si">}</span><span class="s2">.</span><span class="se">\n</span><span class="s2">Allowed strings are:&quot;</span>
-                <span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">pformat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">allowed_strings</span><span class="p">)</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span>
+                <span class="sa">f</span><span class="s2">"Invalid string(s): </span><span class="si">{</span><span class="nb">list</span><span class="p">(</span><span class="n">invalids</span><span class="p">)</span><span class="si">}</span><span class="s2">.</span><span class="se">\n</span><span class="s2">Allowed strings are:"</span>
+                <span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">pformat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">allowed_strings</span><span class="p">)</span><span class="si">}</span><span class="se">\n</span><span class="s2">"</span>
             <span class="p">)</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">duplicates</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">&quot;Duplicate string(s): </span><span class="si">{</span><span class="nb">list</span><span class="p">(</span><span class="n">duplicates</span><span class="p">)</span><span class="si">}</span><span class="s2">.&quot;</span>
+            <span class="n">msg</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">"Duplicate string(s): </span><span class="si">{</span><span class="nb">list</span><span class="p">(</span><span class="n">duplicates</span><span class="p">)</span><span class="si">}</span><span class="s2">."</span>
         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
             <span class="k">raise</span> <span class="n">PropertiesInputValidationError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span></div>
 
@@ -388,17 +388,17 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenTimeSeriesPropertiesList">
 <a class="viewcode-back" href="../../api/types.html#openseries.OpenTimeSeriesPropertiesList">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">OpenTimeSeriesPropertiesList</span><span class="p">(</span><span class="n">PropertiesList</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Allowed property arguments for the OpenTimeSeries class.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Allowed property arguments for the OpenTimeSeries class."""</span>
 
     <span class="n">allowed_strings</span><span class="p">:</span> <span class="n">ClassVar</span><span class="p">[</span><span class="nb">set</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="n">PropertiesList</span><span class="o">.</span><span class="n">allowed_strings</span> <span class="o">|</span> <span class="p">{</span>
-        <span class="s2">&quot;first_idx&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;last_idx&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;length&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;span_of_days&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;yearfrac&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;periods_in_a_year&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;autocorr&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;partial_autocorr&quot;</span><span class="p">,</span>
+        <span class="s2">"first_idx"</span><span class="p">,</span>
+        <span class="s2">"last_idx"</span><span class="p">,</span>
+        <span class="s2">"length"</span><span class="p">,</span>
+        <span class="s2">"span_of_days"</span><span class="p">,</span>
+        <span class="s2">"yearfrac"</span><span class="p">,</span>
+        <span class="s2">"periods_in_a_year"</span><span class="p">,</span>
+        <span class="s2">"autocorr"</span><span class="p">,</span>
+        <span class="s2">"partial_autocorr"</span><span class="p">,</span>
     <span class="p">}</span>
 
 <div class="viewcode-block" id="OpenTimeSeriesPropertiesList.__init__">
@@ -407,7 +407,7 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="o">*</span><span class="n">args</span><span class="p">:</span> <span class="n">LiteralSeriesProps</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Property arguments for the OpenTimeSeries class.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Property arguments for the OpenTimeSeries class."""</span>
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_validate</span><span class="p">()</span></div>
 </div>
@@ -417,20 +417,20 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenFramePropertiesList">
 <a class="viewcode-back" href="../../api/types.html#openseries.OpenFramePropertiesList">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">OpenFramePropertiesList</span><span class="p">(</span><span class="n">PropertiesList</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Allowed property arguments for the OpenFrame class.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Allowed property arguments for the OpenFrame class."""</span>
 
     <span class="n">allowed_strings</span><span class="p">:</span> <span class="n">ClassVar</span><span class="p">[</span><span class="nb">set</span><span class="p">[</span><span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="n">PropertiesList</span><span class="o">.</span><span class="n">allowed_strings</span> <span class="o">|</span> <span class="p">{</span>
-        <span class="s2">&quot;autocorr&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;first_indices&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;last_indices&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;lengths_of_items&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;span_of_days_all&quot;</span><span class="p">,</span>
+        <span class="s2">"autocorr"</span><span class="p">,</span>
+        <span class="s2">"first_indices"</span><span class="p">,</span>
+        <span class="s2">"last_indices"</span><span class="p">,</span>
+        <span class="s2">"lengths_of_items"</span><span class="p">,</span>
+        <span class="s2">"span_of_days_all"</span><span class="p">,</span>
     <span class="p">}</span>
 
 <div class="viewcode-block" id="OpenFramePropertiesList.__init__">
 <a class="viewcode-back" href="../../api/types.html#openseries.OpenFramePropertiesList.__init__">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">:</span> <span class="n">LiteralFrameProps</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Property arguments for the OpenFrame class.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Property arguments for the OpenFrame class."""</span>
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_validate</span><span class="p">()</span></div>
 </div>
@@ -440,153 +440,153 @@ <h1>Source code for openseries.owntypes</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ValueType">
 <a class="viewcode-back" href="../../api/types.html#openseries.ValueType">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">ValueType</span><span class="p">(</span><span class="n">StrEnum</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Enum types of OpenTimeSeries to identify the output.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Enum types of OpenTimeSeries to identify the output."""</span>
 
-    <span class="n">EWMA_VOL</span> <span class="o">=</span> <span class="s2">&quot;EWMA volatility&quot;</span>
-    <span class="n">EWMA_VAR</span> <span class="o">=</span> <span class="s2">&quot;EWMA VaR&quot;</span>
-    <span class="n">PRICE</span> <span class="o">=</span> <span class="s2">&quot;Price(Close)&quot;</span>
-    <span class="n">RTRN</span> <span class="o">=</span> <span class="s2">&quot;Return(Total)&quot;</span>
-    <span class="n">RELRTRN</span> <span class="o">=</span> <span class="s2">&quot;Relative return&quot;</span>
-    <span class="n">ROLLBETA</span> <span class="o">=</span> <span class="s2">&quot;Beta&quot;</span>
-    <span class="n">ROLLCORR</span> <span class="o">=</span> <span class="s2">&quot;Rolling correlation&quot;</span>
-    <span class="n">ROLLCVAR</span> <span class="o">=</span> <span class="s2">&quot;Rolling CVaR&quot;</span>
-    <span class="n">ROLLINFORATIO</span> <span class="o">=</span> <span class="s2">&quot;Information Ratio&quot;</span>
-    <span class="n">ROLLRTRN</span> <span class="o">=</span> <span class="s2">&quot;Rolling returns&quot;</span>
-    <span class="n">ROLLVAR</span> <span class="o">=</span> <span class="s2">&quot;Rolling VaR&quot;</span>
-    <span class="n">ROLLVOL</span> <span class="o">=</span> <span class="s2">&quot;Rolling volatility&quot;</span></div>
+    <span class="n">EWMA_VOL</span> <span class="o">=</span> <span class="s2">"EWMA volatility"</span>
+    <span class="n">EWMA_VAR</span> <span class="o">=</span> <span class="s2">"EWMA VaR"</span>
+    <span class="n">PRICE</span> <span class="o">=</span> <span class="s2">"Price(Close)"</span>
+    <span class="n">RTRN</span> <span class="o">=</span> <span class="s2">"Return(Total)"</span>
+    <span class="n">RELRTRN</span> <span class="o">=</span> <span class="s2">"Relative return"</span>
+    <span class="n">ROLLBETA</span> <span class="o">=</span> <span class="s2">"Beta"</span>
+    <span class="n">ROLLCORR</span> <span class="o">=</span> <span class="s2">"Rolling correlation"</span>
+    <span class="n">ROLLCVAR</span> <span class="o">=</span> <span class="s2">"Rolling CVaR"</span>
+    <span class="n">ROLLINFORATIO</span> <span class="o">=</span> <span class="s2">"Information Ratio"</span>
+    <span class="n">ROLLRTRN</span> <span class="o">=</span> <span class="s2">"Rolling returns"</span>
+    <span class="n">ROLLVAR</span> <span class="o">=</span> <span class="s2">"Rolling VaR"</span>
+    <span class="n">ROLLVOL</span> <span class="o">=</span> <span class="s2">"Rolling volatility"</span></div>
 
 
 
 <div class="viewcode-block" id="MixedValuetypesError">
 <a class="viewcode-back" href="../../api/types.html#openseries.MixedValuetypesError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">MixedValuetypesError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when provided timeseries valuetypes are not the same.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when provided timeseries valuetypes are not the same."""</span></div>
 
 
 
 <div class="viewcode-block" id="AtLeastOneFrameError">
 <a class="viewcode-back" href="../../api/types.html#openseries.AtLeastOneFrameError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">AtLeastOneFrameError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when none of the possible frame inputs is provided.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when none of the possible frame inputs is provided."""</span></div>
 
 
 
 <div class="viewcode-block" id="DateAlignmentError">
 <a class="viewcode-back" href="../../api/types.html#openseries.DateAlignmentError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">DateAlignmentError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when date input is not aligned with existing range.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when date input is not aligned with existing range."""</span></div>
 
 
 
 <div class="viewcode-block" id="NumberOfItemsAndLabelsNotSameError">
 <a class="viewcode-back" href="../../api/types.html#openseries.NumberOfItemsAndLabelsNotSameError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">NumberOfItemsAndLabelsNotSameError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when number of labels is not matching the number of timeseries.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when number of labels is not matching the number of timeseries."""</span></div>
 
 
 
 <div class="viewcode-block" id="InitialValueZeroError">
 <a class="viewcode-back" href="../../api/types.html#openseries.InitialValueZeroError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">InitialValueZeroError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when a calculation cannot be performed due to initial value(s) zero.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when a calculation cannot be performed due to initial value(s) zero."""</span></div>
 
 
 
 <div class="viewcode-block" id="CountriesNotStringNorListStrError">
 <a class="viewcode-back" href="../../api/types.html#openseries.CountriesNotStringNorListStrError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">CountriesNotStringNorListStrError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when countries argument is not provided in correct format.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when countries argument is not provided in correct format."""</span></div>
 
 
 
 <div class="viewcode-block" id="MarketsNotStringNorListStrError">
 <a class="viewcode-back" href="../../api/types.html#openseries.MarketsNotStringNorListStrError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">MarketsNotStringNorListStrError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when markets argument is not provided in correct format.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when markets argument is not provided in correct format."""</span></div>
 
 
 
 <div class="viewcode-block" id="TradingDaysNotAboveZeroError">
 <a class="viewcode-back" href="../../api/types.html#openseries.TradingDaysNotAboveZeroError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">TradingDaysNotAboveZeroError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when trading days argument is not above zero.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when trading days argument is not above zero."""</span></div>
 
 
 
 <div class="viewcode-block" id="BothStartAndEndError">
 <a class="viewcode-back" href="../../api/types.html#openseries.BothStartAndEndError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">BothStartAndEndError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when both start and end dates are provided.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when both start and end dates are provided."""</span></div>
 
 
 
 <div class="viewcode-block" id="NoWeightsError">
 <a class="viewcode-back" href="../../api/types.html#openseries.NoWeightsError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">NoWeightsError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when no weights are provided to function where necessary.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when no weights are provided to function where necessary."""</span></div>
 
 
 
 <div class="viewcode-block" id="LabelsNotUniqueError">
 <a class="viewcode-back" href="../../api/types.html#openseries.LabelsNotUniqueError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">LabelsNotUniqueError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when provided label names are not unique.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when provided label names are not unique."""</span></div>
 
 
 
 <div class="viewcode-block" id="RatioInputError">
 <a class="viewcode-back" href="../../api/types.html#openseries.RatioInputError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">RatioInputError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when ratio keyword not provided correctly.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when ratio keyword not provided correctly."""</span></div>
 
 
 
 <div class="viewcode-block" id="MergingResultedInEmptyError">
 <a class="viewcode-back" href="../../api/types.html#openseries.MergingResultedInEmptyError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">MergingResultedInEmptyError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when a merge resulted in an empty DataFrame.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when a merge resulted in an empty DataFrame."""</span></div>
 
 
 
 <div class="viewcode-block" id="IncorrectArgumentComboError">
 <a class="viewcode-back" href="../../api/types.html#openseries.IncorrectArgumentComboError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">IncorrectArgumentComboError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when correct combination of arguments is not provided.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when correct combination of arguments is not provided."""</span></div>
 
 
 
 <div class="viewcode-block" id="PropertiesInputValidationError">
 <a class="viewcode-back" href="../../api/types.html#openseries.PropertiesInputValidationError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">PropertiesInputValidationError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when duplicate strings are provided.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when duplicate strings are provided."""</span></div>
 
 
 
 <div class="viewcode-block" id="ResampleDataLossError">
 <a class="viewcode-back" href="../../api/types.html#openseries.ResampleDataLossError">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">ResampleDataLossError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when user attempts to run resample_to_business_period_ends on returns.&quot;&quot;&quot;</span></div>
+<span class="w">    </span><span class="sd">"""Raised when user attempts to run resample_to_business_period_ends on returns."""</span></div>
 
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">WeightsNotProvidedError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when weights are not provided.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Raised when weights are not provided."""</span>
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">MultipleCurrenciesError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when multiple currencies are provided.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Raised when multiple currencies are provided."""</span>
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">PortfolioItemsNotWithinFrameError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when portfolio items are not within frame.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Raised when portfolio items are not within frame."""</span>
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">MaxDiversificationNaNError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when max_div weight strategy produces NaN values.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Raised when max_div weight strategy produces NaN values."""</span>
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">MaxDiversificationNegativeWeightsError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Raised when max_div weight strategy produces negative weights.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Raised when max_div weight strategy produces negative weights."""</span>
 </pre></div>
 
            </div>
diff --git a/docs/build/html/_modules/openseries/portfoliotools.html b/docs/build/html/_modules/openseries/portfoliotools.html
index 35896198..7ef4f58a 100644
--- a/docs/build/html/_modules/openseries/portfoliotools.html
+++ b/docs/build/html/_modules/openseries/portfoliotools.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;Defining the portfolio tools for the OpenFrame class.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""Defining the portfolio tools for the OpenFrame class."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -162,11 +162,11 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="kn">from</span><span class="w"> </span><span class="nn">.frame</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenFrame</span>
 
 <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
-    <span class="s2">&quot;constrain_optimized_portfolios&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;efficient_frontier&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;prepare_plot_data&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;sharpeplot&quot;</span><span class="p">,</span>
-    <span class="s2">&quot;simulate_portfolios&quot;</span><span class="p">,</span>
+    <span class="s2">"constrain_optimized_portfolios"</span><span class="p">,</span>
+    <span class="s2">"efficient_frontier"</span><span class="p">,</span>
+    <span class="s2">"prepare_plot_data"</span><span class="p">,</span>
+    <span class="s2">"sharpeplot"</span><span class="p">,</span>
+    <span class="s2">"simulate_portfolios"</span><span class="p">,</span>
 <span class="p">]</span>
 
 
@@ -177,7 +177,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">num_ports</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
     <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate random weights for simulated portfolios.</span>
+<span class="w">    </span><span class="sd">"""Generate random weights for simulated portfolios.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        simframe: Return data for portfolio constituents.</span>
@@ -186,7 +186,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The resulting data.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">copi</span> <span class="o">=</span> <span class="n">simframe</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
 
     <span class="n">vtypes</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">copi</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)]</span>
@@ -196,7 +196,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="k">elif</span> <span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
         <span class="n">log_ret</span> <span class="o">=</span> <span class="n">copi</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
     <span class="k">else</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
         <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="n">log_ret</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">log_ret</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
@@ -209,15 +209,15 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">all_weights</span> <span class="o">=</span> <span class="n">all_weights</span> <span class="o">/</span> <span class="n">all_weights</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
     <span class="n">ret_arr</span> <span class="o">=</span> <span class="n">all_weights</span> <span class="o">@</span> <span class="n">mean_returns</span>
-    <span class="n">vol_arr</span> <span class="o">=</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">einsum</span><span class="p">(</span><span class="s2">&quot;ij,jk,ik-&gt;i&quot;</span><span class="p">,</span> <span class="n">all_weights</span><span class="p">,</span> <span class="n">cov_matrix</span><span class="p">,</span> <span class="n">all_weights</span><span class="p">))</span>
+    <span class="n">vol_arr</span> <span class="o">=</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">einsum</span><span class="p">(</span><span class="s2">"ij,jk,ik-&gt;i"</span><span class="p">,</span> <span class="n">all_weights</span><span class="p">,</span> <span class="n">cov_matrix</span><span class="p">,</span> <span class="n">all_weights</span><span class="p">))</span>
     <span class="n">sharpe_arr</span> <span class="o">=</span> <span class="n">ret_arr</span> <span class="o">/</span> <span class="n">vol_arr</span>
 
     <span class="n">simdf</span> <span class="o">=</span> <span class="n">concat</span><span class="p">(</span>
         <span class="p">[</span>
-            <span class="n">DataFrame</span><span class="p">({</span><span class="s2">&quot;stdev&quot;</span><span class="p">:</span> <span class="n">vol_arr</span><span class="p">,</span> <span class="s2">&quot;ret&quot;</span><span class="p">:</span> <span class="n">ret_arr</span><span class="p">,</span> <span class="s2">&quot;sharpe&quot;</span><span class="p">:</span> <span class="n">sharpe_arr</span><span class="p">}),</span>
+            <span class="n">DataFrame</span><span class="p">({</span><span class="s2">"stdev"</span><span class="p">:</span> <span class="n">vol_arr</span><span class="p">,</span> <span class="s2">"ret"</span><span class="p">:</span> <span class="n">ret_arr</span><span class="p">,</span> <span class="s2">"sharpe"</span><span class="p">:</span> <span class="n">sharpe_arr</span><span class="p">}),</span>
             <span class="n">DataFrame</span><span class="p">(</span><span class="n">all_weights</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">simframe</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">),</span>
         <span class="p">],</span>
-        <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span>
+        <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span>
     <span class="p">)</span>
     <span class="n">simdf</span> <span class="o">=</span> <span class="n">simdf</span><span class="o">.</span><span class="n">replace</span><span class="p">([</span><span class="n">inf</span><span class="p">,</span> <span class="o">-</span><span class="n">inf</span><span class="p">],</span> <span class="n">nan</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">simdf</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span></div>
@@ -225,7 +225,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_prepare_returns_for_frontier</span><span class="p">(</span><span class="n">eframe</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">OpenFrame</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Prepare returns DataFrame for frontier calculation.</span>
+<span class="w">    </span><span class="sd">"""Prepare returns DataFrame for frontier calculation.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        eframe: Portfolio data.</span>
@@ -235,7 +235,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Raises:</span>
 <span class="sd">        MixedValuetypesError: If series types are mixed.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">eframe</span><span class="o">.</span><span class="n">weights</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">eframe</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="p">[</span><span class="mf">1.0</span> <span class="o">/</span> <span class="n">eframe</span><span class="o">.</span><span class="n">item_count</span><span class="p">]</span> <span class="o">*</span> <span class="n">eframe</span><span class="o">.</span><span class="n">item_count</span>
 
@@ -248,7 +248,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="k">elif</span> <span class="nb">all</span><span class="p">(</span><span class="n">vtypes</span><span class="p">):</span>
         <span class="n">log_ret</span> <span class="o">=</span> <span class="n">copi</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
     <span class="k">else</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Mix of series types will give inconsistent results&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Mix of series types will give inconsistent results"</span>
         <span class="k">raise</span> <span class="n">MixedValuetypesError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="n">log_ret</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">log_ret</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
@@ -260,7 +260,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">log_ret</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">periods_in_a_year</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Calculate frontier return bounds.</span>
+<span class="w">    </span><span class="sd">"""Calculate frontier return bounds.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        simulated: Simulated portfolios DataFrame.</span>
@@ -269,9 +269,9 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Tuple of (min_return, max_return).</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">min_stdev_idx</span> <span class="o">=</span> <span class="n">simulated</span><span class="p">[</span><span class="s2">&quot;stdev&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">idxmin</span><span class="p">()</span>
-    <span class="n">frontier_min</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">simulated</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">min_stdev_idx</span><span class="p">,</span> <span class="s2">&quot;ret&quot;</span><span class="p">])</span>
+<span class="sd">    """</span>
+    <span class="n">min_stdev_idx</span> <span class="o">=</span> <span class="n">simulated</span><span class="p">[</span><span class="s2">"stdev"</span><span class="p">]</span><span class="o">.</span><span class="n">idxmin</span><span class="p">()</span>
+    <span class="n">frontier_min</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">simulated</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">min_stdev_idx</span><span class="p">,</span> <span class="s2">"ret"</span><span class="p">])</span>
 
     <span class="n">arithmetic_means</span> <span class="o">=</span> <span class="n">array</span><span class="p">(</span><span class="n">log_ret</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="n">periods_in_a_year</span><span class="p">)</span>
     <span class="n">cleaned_arithmetic_means</span> <span class="o">=</span> <span class="n">arithmetic_means</span><span class="p">[</span><span class="o">~</span><span class="n">isnan</span><span class="p">(</span><span class="n">arithmetic_means</span><span class="p">)]</span>
@@ -290,7 +290,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">bounds</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">],</span> <span class="o">...</span><span class="p">],</span>
     <span class="n">minimize_method</span><span class="p">:</span> <span class="n">LiteralMinimizeMethods</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="nb">list</span><span class="p">[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Build frontier line points.</span>
+<span class="w">    </span><span class="sd">"""Build frontier line points.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        log_ret: Returns DataFrame.</span>
@@ -304,10 +304,10 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Tuple of (frontier_x, frontier_weights).</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_check_sum</span><span class="p">(</span><span class="n">weights</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">npsum</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">npsum</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_get_ret_vol_sr</span><span class="p">(</span>
         <span class="n">lg_ret</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
@@ -317,7 +317,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
         <span class="n">ret</span> <span class="o">=</span> <span class="n">npsum</span><span class="p">(</span><span class="n">lg_ret</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="n">weights</span><span class="p">)</span> <span class="o">*</span> <span class="n">per_in_yr</span>
         <span class="n">volatility</span> <span class="o">=</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">weights</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="p">(</span><span class="n">lg_ret</span><span class="o">.</span><span class="n">cov</span><span class="p">()</span> <span class="o">*</span> <span class="n">per_in_yr</span> <span class="o">@</span> <span class="n">weights</span><span class="p">))</span>
         <span class="n">sr</span> <span class="o">=</span> <span class="n">ret</span> <span class="o">/</span> <span class="n">volatility</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span> <span class="n">array</span><span class="p">([</span><span class="n">ret</span><span class="p">,</span> <span class="n">volatility</span><span class="p">,</span> <span class="n">sr</span><span class="p">]))</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"NDArray[float64]"</span><span class="p">,</span> <span class="n">array</span><span class="p">([</span><span class="n">ret</span><span class="p">,</span> <span class="n">volatility</span><span class="p">,</span> <span class="n">sr</span><span class="p">]))</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_diff_return</span><span class="p">(</span>
         <span class="n">lg_ret</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
@@ -326,7 +326,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
         <span class="n">poss_return</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">float64</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="s2">"float64"</span><span class="p">,</span>
             <span class="n">_get_ret_vol_sr</span><span class="p">(</span><span class="n">lg_ret</span><span class="o">=</span><span class="n">lg_ret</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="n">weights</span><span class="p">,</span> <span class="n">per_in_yr</span><span class="o">=</span><span class="n">per_in_yr</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
             <span class="o">-</span> <span class="n">poss_return</span><span class="p">,</span>
         <span class="p">)</span>
@@ -335,7 +335,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
         <span class="n">weights</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">],</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">float64</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="s2">"float64"</span><span class="p">,</span>
             <span class="n">_get_ret_vol_sr</span><span class="p">(</span>
                 <span class="n">lg_ret</span><span class="o">=</span><span class="n">log_ret</span><span class="p">,</span>
                 <span class="n">weights</span><span class="o">=</span><span class="n">weights</span><span class="p">,</span>
@@ -349,12 +349,12 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
     <span class="k">for</span> <span class="n">possible_return</span> <span class="ow">in</span> <span class="n">frontier_y</span><span class="p">:</span>
         <span class="n">cons</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;Any&quot;</span><span class="p">,</span>
+            <span class="s2">"Any"</span><span class="p">,</span>
             <span class="p">[</span>
-                <span class="p">{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;eq&quot;</span><span class="p">,</span> <span class="s2">&quot;fun&quot;</span><span class="p">:</span> <span class="n">_check_sum</span><span class="p">},</span>
+                <span class="p">{</span><span class="s2">"type"</span><span class="p">:</span> <span class="s2">"eq"</span><span class="p">,</span> <span class="s2">"fun"</span><span class="p">:</span> <span class="n">_check_sum</span><span class="p">},</span>
                 <span class="p">{</span>
-                    <span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;eq&quot;</span><span class="p">,</span>
-                    <span class="s2">&quot;fun&quot;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">w</span><span class="p">,</span> <span class="n">poss_return</span><span class="o">=</span><span class="n">possible_return</span><span class="p">:</span> <span class="n">_diff_return</span><span class="p">(</span>
+                    <span class="s2">"type"</span><span class="p">:</span> <span class="s2">"eq"</span><span class="p">,</span>
+                    <span class="s2">"fun"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">w</span><span class="p">,</span> <span class="n">poss_return</span><span class="o">=</span><span class="n">possible_return</span><span class="p">:</span> <span class="n">_diff_return</span><span class="p">(</span>
                         <span class="n">lg_ret</span><span class="o">=</span><span class="n">log_ret</span><span class="p">,</span>
                         <span class="n">weights</span><span class="o">=</span><span class="n">w</span><span class="p">,</span>
                         <span class="n">per_in_yr</span><span class="o">=</span><span class="n">periods_in_a_year</span><span class="p">,</span>
@@ -372,8 +372,8 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
             <span class="n">constraints</span><span class="o">=</span><span class="n">cons</span><span class="p">,</span>
         <span class="p">)</span>
 
-        <span class="n">frontier_x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s2">&quot;fun&quot;</span><span class="p">])</span>
-        <span class="n">frontier_weights</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s2">&quot;x&quot;</span><span class="p">])</span>
+        <span class="n">frontier_x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s2">"fun"</span><span class="p">])</span>
+        <span class="n">frontier_weights</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s2">"x"</span><span class="p">])</span>
 
     <span class="k">return</span> <span class="n">frontier_x</span><span class="p">,</span> <span class="n">frontier_weights</span>
 
@@ -384,7 +384,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">frontier_weights</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span>
     <span class="n">columns_lvl_zero</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Build frontier DataFrame.</span>
+<span class="w">    </span><span class="sd">"""Build frontier DataFrame.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        frontier_x: Frontier volatility values.</span>
@@ -394,25 +394,25 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Frontier DataFrame.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">line_df</span> <span class="o">=</span> <span class="n">concat</span><span class="p">(</span>
         <span class="p">[</span>
             <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">frontier_weights</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">columns_lvl_zero</span><span class="p">),</span>
-            <span class="n">DataFrame</span><span class="p">({</span><span class="s2">&quot;stdev&quot;</span><span class="p">:</span> <span class="n">frontier_x</span><span class="p">,</span> <span class="s2">&quot;ret&quot;</span><span class="p">:</span> <span class="n">frontier_y</span><span class="p">}),</span>
+            <span class="n">DataFrame</span><span class="p">({</span><span class="s2">"stdev"</span><span class="p">:</span> <span class="n">frontier_x</span><span class="p">,</span> <span class="s2">"ret"</span><span class="p">:</span> <span class="n">frontier_y</span><span class="p">}),</span>
         <span class="p">],</span>
-        <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span>
+        <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span>
     <span class="p">)</span>
-    <span class="n">line_df</span><span class="p">[</span><span class="s2">&quot;sharpe&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">ret</span> <span class="o">/</span> <span class="n">line_df</span><span class="o">.</span><span class="n">stdev</span>
+    <span class="n">line_df</span><span class="p">[</span><span class="s2">"sharpe"</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">ret</span> <span class="o">/</span> <span class="n">line_df</span><span class="o">.</span><span class="n">stdev</span>
 
     <span class="n">limit_small</span> <span class="o">=</span> <span class="mf">0.0001</span>
     <span class="n">line_df</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">mask</span><span class="p">(</span><span class="n">line_df</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span> <span class="o">&lt;</span> <span class="n">limit_small</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
 
     <span class="n">weight_cols</span> <span class="o">=</span> <span class="n">columns_lvl_zero</span>
-    <span class="n">weight_header</span> <span class="o">=</span> <span class="s2">&quot;&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;&quot;</span>
-    <span class="n">line_df</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="p">[</span><span class="n">weight_cols</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>
+    <span class="n">weight_header</span> <span class="o">=</span> <span class="s2">"&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;"</span>
+    <span class="n">line_df</span><span class="p">[</span><span class="s2">"text"</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="p">[</span><span class="n">weight_cols</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>
         <span class="k">lambda</span> <span class="n">row</span><span class="p">:</span> <span class="p">(</span>
             <span class="n">weight_header</span>
-            <span class="o">+</span> <span class="s2">&quot;&lt;br&gt;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">row</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">col</span><span class="si">}</span><span class="s2">&quot;</span> <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">weight_cols</span><span class="p">])</span>
+            <span class="o">+</span> <span class="s2">"&lt;br&gt;"</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">row</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">col</span><span class="si">}</span><span class="s2">"</span> <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">weight_cols</span><span class="p">])</span>
         <span class="p">),</span>
         <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span>
@@ -421,18 +421,18 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_apply_tweak</span><span class="p">(</span><span class="n">line_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Apply tweak to frontier DataFrame.</span>
+<span class="w">    </span><span class="sd">"""Apply tweak to frontier DataFrame.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        line_df: Frontier DataFrame.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Tweaked DataFrame.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">limit_tweak</span> <span class="o">=</span> <span class="mf">0.001</span>
-    <span class="n">line_df</span><span class="p">[</span><span class="s2">&quot;stdev_diff&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">stdev</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
+    <span class="n">line_df</span><span class="p">[</span><span class="s2">"stdev_diff"</span><span class="p">]</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">stdev</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
     <span class="n">line_df</span> <span class="o">=</span> <span class="n">line_df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">line_df</span><span class="o">.</span><span class="n">stdev_diff</span><span class="o">.</span><span class="n">abs</span><span class="p">()</span> <span class="o">&gt;</span> <span class="n">limit_tweak</span><span class="p">]</span>
-    <span class="k">return</span> <span class="n">line_df</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="s2">&quot;stdev_diff&quot;</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">line_df</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="s2">"stdev_diff"</span><span class="p">)</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_create_optimization_functions</span><span class="p">(</span>
@@ -443,7 +443,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">Callable</span><span class="p">[[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span>
     <span class="n">Callable</span><span class="p">[[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span> <span class="n">float64</span><span class="p">],</span>
 <span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Create optimization helper functions.</span>
+<span class="w">    </span><span class="sd">"""Create optimization helper functions.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        log_ret: Returns DataFrame.</span>
@@ -451,19 +451,19 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Tuple of (_check_sum, _get_ret_vol_sr, _neg_sharpe) functions.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_check_sum</span><span class="p">(</span><span class="n">weights</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">npsum</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">npsum</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_get_ret_vol_sr</span><span class="p">(</span><span class="n">weights</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]:</span>
         <span class="n">ret</span> <span class="o">=</span> <span class="n">npsum</span><span class="p">(</span><span class="n">log_ret</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="n">weights</span><span class="p">)</span> <span class="o">*</span> <span class="n">periods_in_a_year</span>
         <span class="n">volatility</span> <span class="o">=</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">weights</span><span class="o">.</span><span class="n">T</span> <span class="o">@</span> <span class="p">(</span><span class="n">log_ret</span><span class="o">.</span><span class="n">cov</span><span class="p">()</span> <span class="o">*</span> <span class="n">periods_in_a_year</span> <span class="o">@</span> <span class="n">weights</span><span class="p">))</span>
         <span class="n">sr</span> <span class="o">=</span> <span class="n">ret</span> <span class="o">/</span> <span class="n">volatility</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span> <span class="n">array</span><span class="p">([</span><span class="n">ret</span><span class="p">,</span> <span class="n">volatility</span><span class="p">,</span> <span class="n">sr</span><span class="p">]))</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"NDArray[float64]"</span><span class="p">,</span> <span class="n">array</span><span class="p">([</span><span class="n">ret</span><span class="p">,</span> <span class="n">volatility</span><span class="p">,</span> <span class="n">sr</span><span class="p">]))</span>
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_neg_sharpe</span><span class="p">(</span><span class="n">weights</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">float64</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span> <span class="n">_get_ret_vol_sr</span><span class="p">(</span><span class="n">weights</span><span class="p">)[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"float64"</span><span class="p">,</span> <span class="n">_get_ret_vol_sr</span><span class="p">(</span><span class="n">weights</span><span class="p">)[</span><span class="mi">2</span><span class="p">]</span> <span class="o">*</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
 
     <span class="k">return</span> <span class="n">_check_sum</span><span class="p">,</span> <span class="n">_get_ret_vol_sr</span><span class="p">,</span> <span class="n">_neg_sharpe</span>
 
@@ -476,7 +476,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">_get_ret_vol_sr</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span>
     <span class="n">_neg_sharpe</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]],</span> <span class="n">float64</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">],</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Optimize maximum Sharpe ratio portfolio.</span>
+<span class="w">    </span><span class="sd">"""Optimize maximum Sharpe ratio portfolio.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        init_guess: Initial guess for optimization.</span>
@@ -488,8 +488,8 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Tuple of (optimal metrics, optimal weights).</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">constraints</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Any&quot;</span><span class="p">,</span> <span class="p">[{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;eq&quot;</span><span class="p">,</span> <span class="s2">&quot;fun&quot;</span><span class="p">:</span> <span class="n">_check_sum</span><span class="p">}])</span>
+<span class="sd">    """</span>
+    <span class="n">constraints</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Any"</span><span class="p">,</span> <span class="p">[{</span><span class="s2">"type"</span><span class="p">:</span> <span class="s2">"eq"</span><span class="p">,</span> <span class="s2">"fun"</span><span class="p">:</span> <span class="n">_check_sum</span><span class="p">}])</span>
     <span class="n">opt_results</span> <span class="o">=</span> <span class="n">minimize</span><span class="p">(</span>
         <span class="n">fun</span><span class="o">=</span><span class="n">_neg_sharpe</span><span class="p">,</span>
         <span class="n">x0</span><span class="o">=</span><span class="n">init_guess</span><span class="p">,</span>
@@ -511,11 +511,11 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">71</span><span class="p">,</span>
     <span class="n">bounds</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">],</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">frontier_points</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">200</span><span class="p">,</span>
-    <span class="n">minimize_method</span><span class="p">:</span> <span class="n">LiteralMinimizeMethods</span> <span class="o">=</span> <span class="s2">&quot;SLSQP&quot;</span><span class="p">,</span>
+    <span class="n">minimize_method</span><span class="p">:</span> <span class="n">LiteralMinimizeMethods</span> <span class="o">=</span> <span class="s2">"SLSQP"</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">tweak</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Identify an efficient frontier.</span>
+<span class="w">    </span><span class="sd">"""Identify an efficient frontier.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        eframe: Portfolio data.</span>
@@ -531,7 +531,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The efficient frontier data, simulation data and optimal portfolio.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">log_ret</span><span class="p">,</span> <span class="n">copi</span> <span class="o">=</span> <span class="n">_prepare_returns_for_frontier</span><span class="p">(</span><span class="n">eframe</span><span class="p">)</span>
 
     <span class="n">simulated</span> <span class="o">=</span> <span class="n">simulate_portfolios</span><span class="p">(</span><span class="n">simframe</span><span class="o">=</span><span class="n">copi</span><span class="p">,</span> <span class="n">num_ports</span><span class="o">=</span><span class="n">num_ports</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
@@ -591,18 +591,18 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 <span class="k">def</span><span class="w"> </span><span class="nf">constrain_optimized_portfolios</span><span class="p">(</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
     <span class="n">serie</span><span class="p">:</span> <span class="n">OpenTimeSeries</span><span class="p">,</span>
-    <span class="n">portfolioname</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;Current Portfolio&quot;</span><span class="p">,</span>
+    <span class="n">portfolioname</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"Current Portfolio"</span><span class="p">,</span>
     <span class="n">simulations</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10000</span><span class="p">,</span>
     <span class="n">curve_points</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">200</span><span class="p">,</span>
     <span class="n">bounds</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">],</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">minimize_method</span><span class="p">:</span> <span class="n">LiteralMinimizeMethods</span> <span class="o">=</span> <span class="s2">&quot;SLSQP&quot;</span><span class="p">,</span>
+    <span class="n">minimize_method</span><span class="p">:</span> <span class="n">LiteralMinimizeMethods</span> <span class="o">=</span> <span class="s2">"SLSQP"</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">OpenFrame</span><span class="p">,</span> <span class="n">OpenTimeSeries</span><span class="p">,</span> <span class="n">OpenFrame</span><span class="p">,</span> <span class="n">OpenTimeSeries</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Constrain optimized portfolios to those that improve on the current one.</span>
+<span class="w">    </span><span class="sd">"""Constrain optimized portfolios to those that improve on the current one.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        data: Portfolio data.</span>
 <span class="sd">        serie: A timeseries representing the current portfolio.</span>
-<span class="sd">        portfolioname: Name of the portfolio. Defaults to &quot;Current Portfolio&quot;.</span>
+<span class="sd">        portfolioname: Name of the portfolio. Defaults to "Current Portfolio".</span>
 <span class="sd">        simulations: Number of possible portfolios to simulate. Defaults to 10000.</span>
 <span class="sd">        curve_points: Number of optimal portfolios on the efficient frontier.</span>
 <span class="sd">            Defaults to 200.</span>
@@ -613,7 +613,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 <span class="sd">    Returns:</span>
 <span class="sd">        The constrained optimal portfolio data.</span>
 
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">lr_frame</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
     <span class="n">mv_frame</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
 
@@ -629,9 +629,9 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="p">)</span>
 
     <span class="n">condition_least_ret</span> <span class="o">=</span> <span class="n">front_frame</span><span class="o">.</span><span class="n">ret</span> <span class="o">&gt;</span> <span class="n">serie</span><span class="o">.</span><span class="n">arithmetic_ret</span>
-    <span class="n">least_ret_frame</span> <span class="o">=</span> <span class="n">front_frame</span><span class="p">[</span><span class="n">condition_least_ret</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span><span class="o">=</span><span class="s2">&quot;stdev&quot;</span><span class="p">)</span>
+    <span class="n">least_ret_frame</span> <span class="o">=</span> <span class="n">front_frame</span><span class="p">[</span><span class="n">condition_least_ret</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span><span class="o">=</span><span class="s2">"stdev"</span><span class="p">)</span>
     <span class="n">least_ret_port</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">least_ret_frame</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
-    <span class="n">least_ret_port_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Minimize vol &amp; target return of </span><span class="si">{</span><span class="n">portfolioname</span><span class="si">}</span><span class="s2">&quot;</span>
+    <span class="n">least_ret_port_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Minimize vol &amp; target return of </span><span class="si">{</span><span class="n">portfolioname</span><span class="si">}</span><span class="s2">"</span>
     <span class="n">least_ret_weights</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span>
         <span class="n">least_ret_port</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">lr_frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span>
     <span class="p">]</span>
@@ -640,11 +640,11 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
     <span class="n">condition_most_vol</span> <span class="o">=</span> <span class="n">front_frame</span><span class="o">.</span><span class="n">stdev</span> <span class="o">&lt;</span> <span class="n">serie</span><span class="o">.</span><span class="n">vol</span>
     <span class="n">most_vol_frame</span> <span class="o">=</span> <span class="n">front_frame</span><span class="p">[</span><span class="n">condition_most_vol</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span>
-        <span class="n">by</span><span class="o">=</span><span class="s2">&quot;ret&quot;</span><span class="p">,</span>
+        <span class="n">by</span><span class="o">=</span><span class="s2">"ret"</span><span class="p">,</span>
         <span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span>
     <span class="n">most_vol_port</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">most_vol_frame</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
-    <span class="n">most_vol_port_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Maximize return &amp; target risk of </span><span class="si">{</span><span class="n">portfolioname</span><span class="si">}</span><span class="s2">&quot;</span>
+    <span class="n">most_vol_port_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Maximize return &amp; target risk of </span><span class="si">{</span><span class="n">portfolioname</span><span class="si">}</span><span class="s2">"</span>
     <span class="n">most_vol_weights</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span>
         <span class="n">most_vol_port</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">mv_frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span>
     <span class="p">]</span>
@@ -662,7 +662,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">current</span><span class="p">:</span> <span class="n">OpenTimeSeries</span><span class="p">,</span>
     <span class="n">optimized</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Prepare data to be used as point_frame in the sharpeplot function.</span>
+<span class="w">    </span><span class="sd">"""Prepare data to be used as point_frame in the sharpeplot function.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        assets: Portfolio data with individual assets and a weighted portfolio.</span>
@@ -671,12 +671,12 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The data prepared with mean returns, volatility and weights.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">txt</span> <span class="o">=</span> <span class="s2">&quot;&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;&quot;</span> <span class="o">+</span> <span class="s2">&quot;&lt;br&gt;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span>
+<span class="sd">    """</span>
+    <span class="n">txt</span> <span class="o">=</span> <span class="s2">"&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;"</span> <span class="o">+</span> <span class="s2">"&lt;br&gt;"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span>
         <span class="p">[</span>
-            <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">wgt</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">nm</span><span class="si">}</span><span class="s2">&quot;</span>
+            <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">wgt</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">nm</span><span class="si">}</span><span class="s2">"</span>
             <span class="k">for</span> <span class="n">wgt</span><span class="p">,</span> <span class="n">nm</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span>
-                <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;list[float]&quot;</span><span class="p">,</span> <span class="n">assets</span><span class="o">.</span><span class="n">weights</span><span class="p">),</span>
+                <span class="n">cast</span><span class="p">(</span><span class="s2">"list[float]"</span><span class="p">,</span> <span class="n">assets</span><span class="o">.</span><span class="n">weights</span><span class="p">),</span>
                 <span class="n">assets</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">,</span>
                 <span class="n">strict</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
             <span class="p">)</span>
@@ -684,23 +684,23 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="p">)</span>
 
     <span class="n">opt_text_list</span> <span class="o">=</span> <span class="p">[</span>
-        <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">wgt</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">nm</span><span class="si">}</span><span class="s2">&quot;</span>
+        <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">wgt</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">  </span><span class="si">{</span><span class="n">nm</span><span class="si">}</span><span class="s2">"</span>
         <span class="k">for</span> <span class="n">wgt</span><span class="p">,</span> <span class="n">nm</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">optimized</span><span class="p">[</span><span class="mi">3</span><span class="p">:],</span> <span class="n">assets</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="p">]</span>
-    <span class="n">opt_text</span> <span class="o">=</span> <span class="s2">&quot;&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;&quot;</span> <span class="o">+</span> <span class="s2">&quot;&lt;br&gt;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">opt_text_list</span><span class="p">)</span>
+    <span class="n">opt_text</span> <span class="o">=</span> <span class="s2">"&lt;br&gt;&lt;br&gt;Weights:&lt;br&gt;"</span> <span class="o">+</span> <span class="s2">"&lt;br&gt;"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">opt_text_list</span><span class="p">)</span>
     <span class="n">plotframe</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span>
         <span class="n">data</span><span class="o">=</span><span class="p">[</span>
             <span class="n">assets</span><span class="o">.</span><span class="n">arithmetic_ret</span><span class="p">,</span>
             <span class="n">assets</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
             <span class="n">Series</span><span class="p">(</span>
-                <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">]</span> <span class="o">*</span> <span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
+                <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">""</span><span class="p">]</span> <span class="o">*</span> <span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
                 <span class="n">index</span><span class="o">=</span><span class="n">assets</span><span class="o">.</span><span class="n">vol</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
             <span class="p">),</span>
         <span class="p">],</span>
-        <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;ret&quot;</span><span class="p">,</span> <span class="s2">&quot;stdev&quot;</span><span class="p">,</span> <span class="s2">&quot;text&quot;</span><span class="p">],</span>
+        <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s2">"ret"</span><span class="p">,</span> <span class="s2">"stdev"</span><span class="p">,</span> <span class="s2">"text"</span><span class="p">],</span>
     <span class="p">)</span>
     <span class="n">plotframe</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">plotframe</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-    <span class="n">plotframe</span><span class="p">[</span><span class="s2">&quot;Max Sharpe Portfolio&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">Series</span><span class="p">(</span>
+    <span class="n">plotframe</span><span class="p">[</span><span class="s2">"Max Sharpe Portfolio"</span><span class="p">]</span> <span class="o">=</span> <span class="n">Series</span><span class="p">(</span>
         <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="n">optimized</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">optimized</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">opt_text</span><span class="p">],</span>
         <span class="n">index</span><span class="o">=</span><span class="n">plotframe</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
         <span class="n">dtype</span><span class="o">=</span><span class="nb">object</span><span class="p">,</span>
@@ -718,18 +718,18 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_determine_output_directory</span><span class="p">(</span><span class="n">directory</span><span class="p">:</span> <span class="n">DirectoryPath</span> <span class="o">|</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Determine output directory for plot file.</span>
+<span class="w">    </span><span class="sd">"""Determine output directory for plot file.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        directory: Optional directory path.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Path to output directory.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">directory</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">Path</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span><span class="o">.</span><span class="n">resolve</span><span class="p">()</span>
-    <span class="k">if</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">&quot;Documents&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
-        <span class="k">return</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">&quot;Documents&quot;</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">"Documents"</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
+        <span class="k">return</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">"Documents"</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">Path</span><span class="p">(</span><span class="n">stack</span><span class="p">()[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">filename</span><span class="p">)</span><span class="o">.</span><span class="n">parent</span>
 
 
@@ -739,30 +739,30 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">returns</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
     <span class="n">risk</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add simulated portfolios trace to figure.</span>
+<span class="w">    </span><span class="sd">"""Add simulated portfolios trace to figure.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        figure: Plotly figure.</span>
 <span class="sd">        sim_frame: Simulated portfolios DataFrame.</span>
 <span class="sd">        returns: List to extend with returns.</span>
 <span class="sd">        risk: List to extend with risk values.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;ret&quot;</span><span class="p">]))</span>
-    <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;stdev&quot;</span><span class="p">]))</span>
+<span class="sd">    """</span>
+    <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"ret"</span><span class="p">]))</span>
+    <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"stdev"</span><span class="p">]))</span>
     <span class="n">figure</span><span class="o">.</span><span class="n">add_scatter</span><span class="p">(</span>
-        <span class="n">x</span><span class="o">=</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;stdev&quot;</span><span class="p">],</span>
-        <span class="n">y</span><span class="o">=</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;ret&quot;</span><span class="p">],</span>
-        <span class="n">hoverinfo</span><span class="o">=</span><span class="s2">&quot;skip&quot;</span><span class="p">,</span>
+        <span class="n">x</span><span class="o">=</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"stdev"</span><span class="p">],</span>
+        <span class="n">y</span><span class="o">=</span><span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"ret"</span><span class="p">],</span>
+        <span class="n">hoverinfo</span><span class="o">=</span><span class="s2">"skip"</span><span class="p">,</span>
         <span class="n">marker</span><span class="o">=</span><span class="p">{</span>
-            <span class="s2">&quot;size&quot;</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span>
-            <span class="s2">&quot;opacity&quot;</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span>
-            <span class="s2">&quot;color&quot;</span><span class="p">:</span> <span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;sharpe&quot;</span><span class="p">],</span>
-            <span class="s2">&quot;colorscale&quot;</span><span class="p">:</span> <span class="s2">&quot;Jet&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;reversescale&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span>
-            <span class="s2">&quot;colorbar&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;thickness&quot;</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">&quot;title&quot;</span><span class="p">:</span> <span class="s2">&quot;Ratio&lt;br&gt;ret / vol&quot;</span><span class="p">},</span>
+            <span class="s2">"size"</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span>
+            <span class="s2">"opacity"</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span>
+            <span class="s2">"color"</span><span class="p">:</span> <span class="n">sim_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"sharpe"</span><span class="p">],</span>
+            <span class="s2">"colorscale"</span><span class="p">:</span> <span class="s2">"Jet"</span><span class="p">,</span>
+            <span class="s2">"reversescale"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span>
+            <span class="s2">"colorbar"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"thickness"</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">"title"</span><span class="p">:</span> <span class="s2">"Ratio&lt;br&gt;ret / vol"</span><span class="p">},</span>
         <span class="p">},</span>
-        <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;markers&quot;</span><span class="p">,</span>
-        <span class="n">name</span><span class="o">=</span><span class="s2">&quot;simulated portfolios&quot;</span><span class="p">,</span>
+        <span class="n">mode</span><span class="o">=</span><span class="s2">"markers"</span><span class="p">,</span>
+        <span class="n">name</span><span class="o">=</span><span class="s2">"simulated portfolios"</span><span class="p">,</span>
     <span class="p">)</span>
 
 
@@ -772,27 +772,27 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">returns</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
     <span class="n">risk</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add efficient frontier trace to figure.</span>
+<span class="w">    </span><span class="sd">"""Add efficient frontier trace to figure.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        figure: Plotly figure.</span>
 <span class="sd">        line_frame: Efficient frontier DataFrame.</span>
 <span class="sd">        returns: List to extend with returns.</span>
 <span class="sd">        risk: List to extend with risk values.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;ret&quot;</span><span class="p">]))</span>
-    <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;stdev&quot;</span><span class="p">]))</span>
+<span class="sd">    """</span>
+    <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"ret"</span><span class="p">]))</span>
+    <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"stdev"</span><span class="p">]))</span>
     <span class="n">figure</span><span class="o">.</span><span class="n">add_scatter</span><span class="p">(</span>
-        <span class="n">x</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;stdev&quot;</span><span class="p">],</span>
-        <span class="n">y</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;ret&quot;</span><span class="p">],</span>
-        <span class="n">text</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;text&quot;</span><span class="p">],</span>
-        <span class="n">xhoverformat</span><span class="o">=</span><span class="s2">&quot;.2%&quot;</span><span class="p">,</span>
-        <span class="n">yhoverformat</span><span class="o">=</span><span class="s2">&quot;.2%&quot;</span><span class="p">,</span>
-        <span class="n">hovertemplate</span><span class="o">=</span><span class="s2">&quot;Return %</span><span class="si">{y}</span><span class="s2">&lt;br&gt;Vol %</span><span class="si">{x}</span><span class="s2">%</span><span class="si">{text}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="n">hoverlabel_align</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span>
-        <span class="n">line</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;width&quot;</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">,</span> <span class="s2">&quot;dash&quot;</span><span class="p">:</span> <span class="s2">&quot;solid&quot;</span><span class="p">},</span>
-        <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;lines&quot;</span><span class="p">,</span>
-        <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Efficient frontier&quot;</span><span class="p">,</span>
+        <span class="n">x</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"stdev"</span><span class="p">],</span>
+        <span class="n">y</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"ret"</span><span class="p">],</span>
+        <span class="n">text</span><span class="o">=</span><span class="n">line_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"text"</span><span class="p">],</span>
+        <span class="n">xhoverformat</span><span class="o">=</span><span class="s2">".2%"</span><span class="p">,</span>
+        <span class="n">yhoverformat</span><span class="o">=</span><span class="s2">".2%"</span><span class="p">,</span>
+        <span class="n">hovertemplate</span><span class="o">=</span><span class="s2">"Return %</span><span class="si">{y}</span><span class="s2">&lt;br&gt;Vol %</span><span class="si">{x}</span><span class="s2">%</span><span class="si">{text}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="n">hoverlabel_align</span><span class="o">=</span><span class="s2">"right"</span><span class="p">,</span>
+        <span class="n">line</span><span class="o">=</span><span class="p">{</span><span class="s2">"width"</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">,</span> <span class="s2">"dash"</span><span class="p">:</span> <span class="s2">"solid"</span><span class="p">},</span>
+        <span class="n">mode</span><span class="o">=</span><span class="s2">"lines"</span><span class="p">,</span>
+        <span class="n">name</span><span class="o">=</span><span class="s2">"Efficient frontier"</span><span class="p">,</span>
     <span class="p">)</span>
 
 
@@ -804,7 +804,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">returns</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
     <span class="n">risk</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add point frame traces to figure.</span>
+<span class="w">    </span><span class="sd">"""Add point frame traces to figure.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        figure: Plotly figure.</span>
@@ -813,12 +813,12 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 <span class="sd">        fig: Plotly figure dictionary.</span>
 <span class="sd">        returns: List to extend with returns.</span>
 <span class="sd">        risk: List to extend with risk values.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">layout_dict</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-        <span class="s2">&quot;dict[str, str | int | float | bool | list[str]]&quot;</span><span class="p">,</span>
-        <span class="n">fig</span><span class="p">[</span><span class="s2">&quot;layout&quot;</span><span class="p">],</span>
+        <span class="s2">"dict[str, str | int | float | bool | list[str]]"</span><span class="p">,</span>
+        <span class="n">fig</span><span class="p">[</span><span class="s2">"layout"</span><span class="p">],</span>
     <span class="p">)</span>
-    <span class="n">base_colorway</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;list[str]&quot;</span><span class="p">,</span> <span class="n">layout_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;colorway&quot;</span><span class="p">,</span> <span class="p">[]))</span>
+    <span class="n">base_colorway</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"list[str]"</span><span class="p">,</span> <span class="n">layout_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"colorway"</span><span class="p">,</span> <span class="p">[]))</span>
     <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">base_colorway</span><span class="p">)</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">point_frame</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span> <span class="ow">and</span> <span class="n">base_colorway</span><span class="p">:</span>
         <span class="n">repeats</span> <span class="o">=</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">point_frame</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">base_colorway</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="nb">len</span><span class="p">(</span>
             <span class="n">base_colorway</span>
@@ -827,22 +827,22 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">colorway</span> <span class="o">=</span> <span class="n">base_colorway</span><span class="p">[:</span> <span class="nb">len</span><span class="p">(</span><span class="n">point_frame</span><span class="o">.</span><span class="n">columns</span><span class="p">)]</span>
     <span class="k">for</span> <span class="n">col</span><span class="p">,</span> <span class="n">clr</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">point_frame</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span> <span class="n">colorway</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
-        <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;ret&quot;</span><span class="p">,</span> <span class="n">col</span><span class="p">])])</span>
-        <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;stdev&quot;</span><span class="p">,</span> <span class="n">col</span><span class="p">])])</span>
+        <span class="n">returns</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"ret"</span><span class="p">,</span> <span class="n">col</span><span class="p">])])</span>
+        <span class="n">risk</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"stdev"</span><span class="p">,</span> <span class="n">col</span><span class="p">])])</span>
         <span class="n">figure</span><span class="o">.</span><span class="n">add_scatter</span><span class="p">(</span>
-            <span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;stdev&quot;</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
-            <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;ret&quot;</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
-            <span class="n">xhoverformat</span><span class="o">=</span><span class="s2">&quot;.2%&quot;</span><span class="p">,</span>
-            <span class="n">yhoverformat</span><span class="o">=</span><span class="s2">&quot;.2%&quot;</span><span class="p">,</span>
-            <span class="n">hovertext</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;text&quot;</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
-            <span class="n">hovertemplate</span><span class="o">=</span><span class="s2">&quot;Return %</span><span class="si">{y}</span><span class="s2">&lt;br&gt;Vol %</span><span class="si">{x}</span><span class="s2">%</span><span class="si">{hovertext}</span><span class="s2">&quot;</span><span class="p">,</span>
-            <span class="n">hoverlabel_align</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span>
-            <span class="n">marker</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;size&quot;</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">&quot;color&quot;</span><span class="p">:</span> <span class="n">clr</span><span class="p">},</span>
+            <span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"stdev"</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
+            <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"ret"</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
+            <span class="n">xhoverformat</span><span class="o">=</span><span class="s2">".2%"</span><span class="p">,</span>
+            <span class="n">yhoverformat</span><span class="o">=</span><span class="s2">".2%"</span><span class="p">,</span>
+            <span class="n">hovertext</span><span class="o">=</span><span class="p">[</span><span class="n">point_frame</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">"text"</span><span class="p">,</span> <span class="n">col</span><span class="p">]],</span>
+            <span class="n">hovertemplate</span><span class="o">=</span><span class="s2">"Return %</span><span class="si">{y}</span><span class="s2">&lt;br&gt;Vol %</span><span class="si">{x}</span><span class="s2">%</span><span class="si">{hovertext}</span><span class="s2">"</span><span class="p">,</span>
+            <span class="n">hoverlabel_align</span><span class="o">=</span><span class="s2">"right"</span><span class="p">,</span>
+            <span class="n">marker</span><span class="o">=</span><span class="p">{</span><span class="s2">"size"</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">"color"</span><span class="p">:</span> <span class="n">clr</span><span class="p">},</span>
             <span class="n">mode</span><span class="o">=</span><span class="n">point_frame_mode</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="n">col</span><span class="p">,</span>
             <span class="n">text</span><span class="o">=</span><span class="n">col</span><span class="p">,</span>
-            <span class="n">textfont</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;size&quot;</span><span class="p">:</span> <span class="mi">14</span><span class="p">},</span>
-            <span class="n">textposition</span><span class="o">=</span><span class="s2">&quot;bottom center&quot;</span><span class="p">,</span>
+            <span class="n">textfont</span><span class="o">=</span><span class="p">{</span><span class="s2">"size"</span><span class="p">:</span> <span class="mi">14</span><span class="p">},</span>
+            <span class="n">textposition</span><span class="o">=</span><span class="s2">"bottom center"</span><span class="p">,</span>
         <span class="p">)</span>
 
 
@@ -854,7 +854,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">title</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="n">add_logo</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Configure figure layout.</span>
+<span class="w">    </span><span class="sd">"""Configure figure layout.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        figure: Plotly figure.</span>
@@ -862,22 +862,22 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 <span class="sd">        titletext: Optional title text.</span>
 <span class="sd">        add_logo: Whether to add logo.</span>
 <span class="sd">        logo: Logo dictionary.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">figure</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span>
-        <span class="n">xaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;tickformat&quot;</span><span class="p">:</span> <span class="s2">&quot;.1%&quot;</span><span class="p">},</span>
-        <span class="n">xaxis_title</span><span class="o">=</span><span class="s2">&quot;volatility&quot;</span><span class="p">,</span>
+        <span class="n">xaxis</span><span class="o">=</span><span class="p">{</span><span class="s2">"tickformat"</span><span class="p">:</span> <span class="s2">".1%"</span><span class="p">},</span>
+        <span class="n">xaxis_title</span><span class="o">=</span><span class="s2">"volatility"</span><span class="p">,</span>
         <span class="n">yaxis</span><span class="o">=</span><span class="p">{</span>
-            <span class="s2">&quot;tickformat&quot;</span><span class="p">:</span> <span class="s2">&quot;.1%&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;scaleanchor&quot;</span><span class="p">:</span> <span class="s2">&quot;x&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;scaleratio&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
+            <span class="s2">"tickformat"</span><span class="p">:</span> <span class="s2">".1%"</span><span class="p">,</span>
+            <span class="s2">"scaleanchor"</span><span class="p">:</span> <span class="s2">"x"</span><span class="p">,</span>
+            <span class="s2">"scaleratio"</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
         <span class="p">},</span>
-        <span class="n">yaxis_title</span><span class="o">=</span><span class="s2">&quot;annual return&quot;</span><span class="p">,</span>
+        <span class="n">yaxis_title</span><span class="o">=</span><span class="s2">"annual return"</span><span class="p">,</span>
         <span class="n">showlegend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span>
     <span class="k">if</span> <span class="n">title</span><span class="p">:</span>
         <span class="k">if</span> <span class="n">titletext</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">titletext</span> <span class="o">=</span> <span class="s2">&quot;&lt;b&gt;Risk and Return&lt;/b&gt;&lt;br&gt;&quot;</span>
-        <span class="n">figure</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;text&quot;</span><span class="p">:</span> <span class="n">titletext</span><span class="p">,</span> <span class="s2">&quot;font&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;size&quot;</span><span class="p">:</span> <span class="mi">36</span><span class="p">}})</span>
+            <span class="n">titletext</span> <span class="o">=</span> <span class="s2">"&lt;b&gt;Risk and Return&lt;/b&gt;&lt;br&gt;"</span>
+        <span class="n">figure</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">title</span><span class="o">=</span><span class="p">{</span><span class="s2">"text"</span><span class="p">:</span> <span class="n">titletext</span><span class="p">,</span> <span class="s2">"font"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"size"</span><span class="p">:</span> <span class="mi">36</span><span class="p">}})</span>
 
     <span class="k">if</span> <span class="n">add_logo</span><span class="p">:</span>
         <span class="n">figure</span><span class="o">.</span><span class="n">add_layout_image</span><span class="p">(</span><span class="n">logo</span><span class="p">)</span>
@@ -893,7 +893,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate output for sharpeplot.</span>
+<span class="w">    </span><span class="sd">"""Generate output for sharpeplot.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        figure: Plotly figure.</span>
@@ -906,26 +906,26 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Output string.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">if</span> <span class="n">output_type</span> <span class="o">==</span> <span class="s2">&quot;file&quot;</span><span class="p">:</span>
+<span class="sd">    """</span>
+    <span class="k">if</span> <span class="n">output_type</span> <span class="o">==</span> <span class="s2">"file"</span><span class="p">:</span>
         <span class="n">plot</span><span class="p">(</span>
             <span class="n">figure_or_data</span><span class="o">=</span><span class="n">figure</span><span class="p">,</span>
             <span class="n">filename</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">plotfile</span><span class="p">),</span>
             <span class="n">auto_open</span><span class="o">=</span><span class="n">auto_open</span><span class="p">,</span>
             <span class="n">auto_play</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
-            <span class="n">link_text</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
+            <span class="n">link_text</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span>
             <span class="n">include_plotlyjs</span><span class="o">=</span><span class="n">include_plotlyjs</span><span class="p">,</span>
-            <span class="n">config</span><span class="o">=</span><span class="n">fig</span><span class="p">[</span><span class="s2">&quot;config&quot;</span><span class="p">],</span>
+            <span class="n">config</span><span class="o">=</span><span class="n">fig</span><span class="p">[</span><span class="s2">"config"</span><span class="p">],</span>
             <span class="n">output_type</span><span class="o">=</span><span class="n">output_type</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="n">plotfile</span><span class="p">)</span>
 
-    <span class="n">div_id</span> <span class="o">=</span> <span class="n">filename</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="n">maxsplit</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s2">&quot;.&quot;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+    <span class="n">div_id</span> <span class="o">=</span> <span class="n">filename</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="n">maxsplit</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s2">"."</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
     <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-        <span class="s2">&quot;str&quot;</span><span class="p">,</span>
+        <span class="s2">"str"</span><span class="p">,</span>
         <span class="n">to_html</span><span class="p">(</span>
             <span class="n">fig</span><span class="o">=</span><span class="n">figure</span><span class="p">,</span>
-            <span class="n">config</span><span class="o">=</span><span class="n">fig</span><span class="p">[</span><span class="s2">&quot;config&quot;</span><span class="p">],</span>
+            <span class="n">config</span><span class="o">=</span><span class="n">fig</span><span class="p">[</span><span class="s2">"config"</span><span class="p">],</span>
             <span class="n">auto_play</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
             <span class="n">include_plotlyjs</span><span class="o">=</span><span class="n">include_plotlyjs</span><span class="p">,</span>
             <span class="n">full_html</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
@@ -940,18 +940,18 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
     <span class="n">sim_frame</span><span class="p">:</span> <span class="n">DataFrame</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">line_frame</span><span class="p">:</span> <span class="n">DataFrame</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">point_frame</span><span class="p">:</span> <span class="n">DataFrame</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">point_frame_mode</span><span class="p">:</span> <span class="n">LiteralLinePlotMode</span> <span class="o">=</span> <span class="s2">&quot;markers&quot;</span><span class="p">,</span>
+    <span class="n">point_frame_mode</span><span class="p">:</span> <span class="n">LiteralLinePlotMode</span> <span class="o">=</span> <span class="s2">"markers"</span><span class="p">,</span>
     <span class="n">filename</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">directory</span><span class="p">:</span> <span class="n">DirectoryPath</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">titletext</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">output_type</span><span class="p">:</span> <span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="s2">&quot;file&quot;</span><span class="p">,</span>
-    <span class="n">include_plotlyjs</span><span class="p">:</span> <span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="s2">&quot;cdn&quot;</span><span class="p">,</span>
+    <span class="n">output_type</span><span class="p">:</span> <span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="s2">"file"</span><span class="p">,</span>
+    <span class="n">include_plotlyjs</span><span class="p">:</span> <span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="s2">"cdn"</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">title</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="n">add_logo</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">Figure</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Create scatter plot coloured by Sharpe Ratio.</span>
+<span class="w">    </span><span class="sd">"""Create scatter plot coloured by Sharpe Ratio.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        sim_frame: Data from the simulate_portfolios method.</span>
@@ -961,10 +961,10 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 <span class="sd">        filename: Name of the Plotly html file.</span>
 <span class="sd">        directory: Directory where Plotly html file is saved.</span>
 <span class="sd">        titletext: Text for the plot title.</span>
-<span class="sd">        output_type: Determines output type. Defaults to &quot;file&quot;.</span>
+<span class="sd">        output_type: Determines output type. Defaults to "file".</span>
 <span class="sd">        include_plotlyjs: Determines how the plotly.js library is included</span>
 <span class="sd">            in the output.</span>
-<span class="sd">            Defaults to &quot;cdn&quot;.</span>
+<span class="sd">            Defaults to "cdn".</span>
 <span class="sd">        title: Whether to add standard plot title. Defaults to True.</span>
 <span class="sd">        add_logo: Whether to add Captor logo. Defaults to True.</span>
 <span class="sd">        auto_open: Determines whether to open a browser window with the plot.</span>
@@ -972,9 +972,9 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        The scatter plot with simulated and optimized results.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">sim_frame</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">line_frame</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">point_frame</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;One of sim_frame, line_frame or point_frame must be provided.&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"One of sim_frame, line_frame or point_frame must be provided."</span>
         <span class="k">raise</span> <span class="n">AtLeastOneFrameError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="n">returns</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
@@ -982,7 +982,7 @@ <h1>Source code for openseries.portfoliotools</h1><div class="highlight"><pre>
 
     <span class="n">dirpath</span> <span class="o">=</span> <span class="n">_determine_output_directory</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span>
     <span class="k">if</span> <span class="ow">not</span> <span class="n">filename</span><span class="p">:</span>
-        <span class="n">filename</span> <span class="o">=</span> <span class="s2">&quot;sharpeplot.html&quot;</span>
+        <span class="n">filename</span> <span class="o">=</span> <span class="s2">"sharpeplot.html"</span>
     <span class="n">plotfile</span> <span class="o">=</span> <span class="n">dirpath</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span>
 
     <span class="n">fig</span><span class="p">,</span> <span class="n">logo</span> <span class="o">=</span> <span class="n">load_plotly_dict</span><span class="p">()</span>
diff --git a/docs/build/html/_modules/openseries/report.html b/docs/build/html/_modules/openseries/report.html
index 5a58c3ea..44cd0985 100644
--- a/docs/build/html/_modules/openseries/report.html
+++ b/docs/build/html/_modules/openseries/report.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.report</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;Functions related to HTML reports.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""Functions related to HTML reports."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -143,29 +143,29 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
 
 <span class="n">logger</span> <span class="o">=</span> <span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;report_html&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"report_html"</span><span class="p">]</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">calendar_period_returns</span><span class="p">(</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
-    <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">&quot;BYE&quot;</span><span class="p">,</span>
+    <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">"BYE"</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">relabel</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate a table of returns with appropriate table labels.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Generate a table of returns with appropriate table labels."""</span>
     <span class="n">copied</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
     <span class="n">copied</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
     <span class="n">copied</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
     <span class="n">cldr</span> <span class="o">=</span> <span class="n">copied</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
     <span class="k">if</span> <span class="n">relabel</span><span class="p">:</span>
-        <span class="k">if</span> <span class="n">freq</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span> <span class="o">==</span> <span class="s2">&quot;BYE&quot;</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">freq</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span> <span class="o">==</span> <span class="s2">"BYE"</span><span class="p">:</span>
             <span class="n">cldr</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">([</span><span class="n">d</span><span class="o">.</span><span class="n">year</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">cldr</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
-        <span class="k">elif</span> <span class="n">freq</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span> <span class="o">==</span> <span class="s2">&quot;BQE&quot;</span><span class="p">:</span>
+        <span class="k">elif</span> <span class="n">freq</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span> <span class="o">==</span> <span class="s2">"BQE"</span><span class="p">:</span>
             <span class="n">cldr</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">(</span>
-                <span class="p">[</span><span class="n">Timestamp</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">to_period</span><span class="p">(</span><span class="s2">&quot;Q&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;Q%q %Y&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">cldr</span><span class="o">.</span><span class="n">index</span><span class="p">],</span>
+                <span class="p">[</span><span class="n">Timestamp</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">to_period</span><span class="p">(</span><span class="s2">"Q"</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"Q%q %Y"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">cldr</span><span class="o">.</span><span class="n">index</span><span class="p">],</span>
             <span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">cldr</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">([</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%b %y&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">cldr</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
+            <span class="n">cldr</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">([</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%b %y"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">cldr</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
     <span class="k">return</span> <span class="n">cldr</span>
 
 
@@ -174,100 +174,100 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_fmt_dates</span><span class="p">(</span><span class="n">idx</span><span class="p">:</span> <span class="n">Index</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span>
-    <span class="k">return</span> <span class="p">[</span><span class="n">Timestamp</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">idx</span><span class="p">]</span>
+    <span class="k">return</span> <span class="p">[</span><span class="n">Timestamp</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">idx</span><span class="p">]</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_metrics_table_html</span><span class="p">(</span><span class="n">df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-    <span class="k">return</span> <span class="n">df</span><span class="o">.</span><span class="n">to_html</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">escape</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;metrics&quot;</span><span class="p">],</span> <span class="n">border</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">df</span><span class="o">.</span><span class="n">to_html</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">escape</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s2">"metrics"</span><span class="p">],</span> <span class="n">border</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_get_report_properties_and_labels</span><span class="p">(</span>
     <span class="n">yearfrac</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get properties and labels based on yearfrac.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Get properties and labels based on yearfrac."""</span>
     <span class="k">if</span> <span class="n">yearfrac</span> <span class="o">&gt;</span> <span class="mf">1.0</span><span class="p">:</span>
         <span class="n">properties</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;geo_ret&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;vol&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;ret_vol_ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;sortino_ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;worst_month&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;first_indices&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;last_indices&quot;</span><span class="p">,</span>
+            <span class="s2">"geo_ret"</span><span class="p">,</span>
+            <span class="s2">"vol"</span><span class="p">,</span>
+            <span class="s2">"ret_vol_ratio"</span><span class="p">,</span>
+            <span class="s2">"sortino_ratio"</span><span class="p">,</span>
+            <span class="s2">"worst_month"</span><span class="p">,</span>
+            <span class="s2">"first_indices"</span><span class="p">,</span>
+            <span class="s2">"last_indices"</span><span class="p">,</span>
         <span class="p">]</span>
         <span class="n">labels_init</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;Return (CAGR)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Volatility&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sharpe Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sortino Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Worst Month&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison Start&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison End&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Information Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Capture Ratio (monthly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">,</span>
+            <span class="s2">"Return (CAGR)"</span><span class="p">,</span>
+            <span class="s2">"Volatility"</span><span class="p">,</span>
+            <span class="s2">"Sharpe Ratio"</span><span class="p">,</span>
+            <span class="s2">"Sortino Ratio"</span><span class="p">,</span>
+            <span class="s2">"Worst Month"</span><span class="p">,</span>
+            <span class="s2">"Comparison Start"</span><span class="p">,</span>
+            <span class="s2">"Comparison End"</span><span class="p">,</span>
+            <span class="s2">"Jensen's Alpha"</span><span class="p">,</span>
+            <span class="s2">"Information Ratio"</span><span class="p">,</span>
+            <span class="s2">"Tracking Error (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Capture Ratio (monthly)"</span><span class="p">,</span>
+            <span class="s2">"Index Beta (weekly)"</span><span class="p">,</span>
         <span class="p">]</span>
         <span class="n">labels_final</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;Return (CAGR)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Year-to-Date&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Month-to-Date&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Volatility&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sharpe Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sortino Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Information Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Capture Ratio (monthly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Worst Month&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison Start&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison End&quot;</span><span class="p">,</span>
+            <span class="s2">"Return (CAGR)"</span><span class="p">,</span>
+            <span class="s2">"Year-to-Date"</span><span class="p">,</span>
+            <span class="s2">"Month-to-Date"</span><span class="p">,</span>
+            <span class="s2">"Volatility"</span><span class="p">,</span>
+            <span class="s2">"Sharpe Ratio"</span><span class="p">,</span>
+            <span class="s2">"Sortino Ratio"</span><span class="p">,</span>
+            <span class="s2">"Jensen's Alpha"</span><span class="p">,</span>
+            <span class="s2">"Information Ratio"</span><span class="p">,</span>
+            <span class="s2">"Tracking Error (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Index Beta (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Capture Ratio (monthly)"</span><span class="p">,</span>
+            <span class="s2">"Worst Month"</span><span class="p">,</span>
+            <span class="s2">"Comparison Start"</span><span class="p">,</span>
+            <span class="s2">"Comparison End"</span><span class="p">,</span>
         <span class="p">]</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">properties</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;value_ret&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;vol&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;ret_vol_ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;sortino_ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;worst&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;first_indices&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;last_indices&quot;</span><span class="p">,</span>
+            <span class="s2">"value_ret"</span><span class="p">,</span>
+            <span class="s2">"vol"</span><span class="p">,</span>
+            <span class="s2">"ret_vol_ratio"</span><span class="p">,</span>
+            <span class="s2">"sortino_ratio"</span><span class="p">,</span>
+            <span class="s2">"worst"</span><span class="p">,</span>
+            <span class="s2">"first_indices"</span><span class="p">,</span>
+            <span class="s2">"last_indices"</span><span class="p">,</span>
         <span class="p">]</span>
         <span class="n">labels_init</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;Return (simple)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Volatility&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sharpe Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sortino Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Worst Day&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison Start&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison End&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Information Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">,</span>
+            <span class="s2">"Return (simple)"</span><span class="p">,</span>
+            <span class="s2">"Volatility"</span><span class="p">,</span>
+            <span class="s2">"Sharpe Ratio"</span><span class="p">,</span>
+            <span class="s2">"Sortino Ratio"</span><span class="p">,</span>
+            <span class="s2">"Worst Day"</span><span class="p">,</span>
+            <span class="s2">"Comparison Start"</span><span class="p">,</span>
+            <span class="s2">"Comparison End"</span><span class="p">,</span>
+            <span class="s2">"Jensen's Alpha"</span><span class="p">,</span>
+            <span class="s2">"Information Ratio"</span><span class="p">,</span>
+            <span class="s2">"Tracking Error (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Index Beta (weekly)"</span><span class="p">,</span>
         <span class="p">]</span>
         <span class="n">labels_final</span> <span class="o">=</span> <span class="p">[</span>
-            <span class="s2">&quot;Return (simple)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Year-to-Date&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Month-to-Date&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Volatility&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sharpe Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Sortino Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Information Ratio&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Worst Day&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison Start&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;Comparison End&quot;</span><span class="p">,</span>
+            <span class="s2">"Return (simple)"</span><span class="p">,</span>
+            <span class="s2">"Year-to-Date"</span><span class="p">,</span>
+            <span class="s2">"Month-to-Date"</span><span class="p">,</span>
+            <span class="s2">"Volatility"</span><span class="p">,</span>
+            <span class="s2">"Sharpe Ratio"</span><span class="p">,</span>
+            <span class="s2">"Sortino Ratio"</span><span class="p">,</span>
+            <span class="s2">"Jensen's Alpha"</span><span class="p">,</span>
+            <span class="s2">"Information Ratio"</span><span class="p">,</span>
+            <span class="s2">"Tracking Error (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Index Beta (weekly)"</span><span class="p">,</span>
+            <span class="s2">"Worst Day"</span><span class="p">,</span>
+            <span class="s2">"Comparison Start"</span><span class="p">,</span>
+            <span class="s2">"Comparison End"</span><span class="p">,</span>
         <span class="p">]</span>
     <span class="k">return</span> <span class="n">properties</span><span class="p">,</span> <span class="n">labels_init</span><span class="p">,</span> <span class="n">labels_final</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_create_line_traces</span><span class="p">(</span><span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">Scatter</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Create line traces for the plot.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Create line traces for the plot."""</span>
     <span class="n">x_line</span> <span class="o">=</span> <span class="n">_fmt_dates</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
     <span class="n">line_traces</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Scatter</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
     <span class="k">for</span> <span class="n">item</span><span class="p">,</span> <span class="n">lbl</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">):</span>
@@ -275,9 +275,9 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
             <span class="n">Scatter</span><span class="p">(</span>
                 <span class="n">x</span><span class="o">=</span><span class="n">x_line</span><span class="p">,</span>
                 <span class="n">y</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">item</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
-                <span class="n">hovertemplate</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">lbl</span><span class="si">}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">y:.2%</span><span class="se">}}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">x</span><span class="se">}}</span><span class="s2">&lt;extra&gt;&lt;/extra&gt;&quot;</span><span class="p">,</span>
-                <span class="n">line</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;width&quot;</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">,</span> <span class="s2">&quot;dash&quot;</span><span class="p">:</span> <span class="s2">&quot;solid&quot;</span><span class="p">},</span>
-                <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;lines&quot;</span><span class="p">,</span>
+                <span class="n">hovertemplate</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">lbl</span><span class="si">}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">y:.2%</span><span class="se">}}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">x</span><span class="se">}}</span><span class="s2">&lt;extra&gt;&lt;/extra&gt;"</span><span class="p">,</span>
+                <span class="n">line</span><span class="o">=</span><span class="p">{</span><span class="s2">"width"</span><span class="p">:</span> <span class="mf">2.5</span><span class="p">,</span> <span class="s2">"dash"</span><span class="p">:</span> <span class="s2">"solid"</span><span class="p">},</span>
+                <span class="n">mode</span><span class="o">=</span><span class="s2">"lines"</span><span class="p">,</span>
                 <span class="n">name</span><span class="o">=</span><span class="n">lbl</span><span class="p">,</span>
                 <span class="n">showlegend</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
             <span class="p">),</span>
@@ -289,7 +289,7 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
     <span class="n">bar_freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">Bar</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Create bar traces for the plot.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Create bar traces for the plot."""</span>
     <span class="n">quarter_of_year</span> <span class="o">=</span> <span class="mf">0.25</span>
     <span class="k">if</span> <span class="n">data</span><span class="o">.</span><span class="n">yearfrac</span> <span class="o">&lt;</span> <span class="n">quarter_of_year</span><span class="p">:</span>
         <span class="n">tmp</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
@@ -300,12 +300,12 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">x_bar</span> <span class="o">=</span> <span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">bdf</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
     <span class="n">bar_traces</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Bar</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
     <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">item_count</span><span class="p">):</span>
-        <span class="n">col_name</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;tuple[str, ValueType]&quot;</span><span class="p">,</span> <span class="n">bdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">item</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
+        <span class="n">col_name</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"tuple[str, ValueType]"</span><span class="p">,</span> <span class="n">bdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">item</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
         <span class="n">bar_traces</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
             <span class="n">Bar</span><span class="p">(</span>
                 <span class="n">x</span><span class="o">=</span><span class="n">x_bar</span><span class="p">,</span>
                 <span class="n">y</span><span class="o">=</span><span class="n">bdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="n">item</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span>
-                <span class="n">hovertemplate</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">col_name</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">y:.2%</span><span class="se">}}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">x</span><span class="se">}}</span><span class="s2">&lt;extra&gt;&lt;/extra&gt;&quot;</span><span class="p">,</span>
+                <span class="n">hovertemplate</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">col_name</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">y:.2%</span><span class="se">}}</span><span class="s2">&lt;br&gt;%</span><span class="se">{{</span><span class="s2">x</span><span class="se">}}</span><span class="s2">&lt;extra&gt;&lt;/extra&gt;"</span><span class="p">,</span>
                 <span class="n">name</span><span class="o">=</span><span class="n">col_name</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span>
                 <span class="n">showlegend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
             <span class="p">),</span>
@@ -317,11 +317,11 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Jensen&#39;s Alpha to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Jensen's Alpha to the report dataframe."""</span>
     <span class="n">alpha_frame</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
     <span class="n">alpha_frame</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>
     <span class="k">with</span> <span class="n">catch_warnings</span><span class="p">():</span>
-        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
+        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
         <span class="n">alphas</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span> <span class="o">|</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span>
             <span class="n">alpha_frame</span><span class="o">.</span><span class="n">jensen_alpha</span><span class="p">(</span>
                 <span class="n">asset</span><span class="o">=</span><span class="p">(</span><span class="n">aname</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">),</span>
@@ -330,11 +330,11 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
             <span class="p">)</span>
             <span class="k">for</span> <span class="n">aname</span> <span class="ow">in</span> <span class="n">alpha_frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
         <span class="p">]</span>
-    <span class="n">alphas</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
+    <span class="n">alphas</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
     <span class="n">ar</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span>
         <span class="n">data</span><span class="o">=</span><span class="n">alphas</span><span class="p">,</span>
         <span class="n">index</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-        <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">],</span>
+        <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"Jensen's Alpha"</span><span class="p">],</span>
     <span class="p">)</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">ar</span><span class="p">])</span>
 
@@ -343,9 +343,9 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Information Ratio to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Information Ratio to the report dataframe."""</span>
     <span class="n">ir</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">info_ratio_func</span><span class="p">()</span>
-    <span class="n">ir</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Information Ratio&quot;</span>
+    <span class="n">ir</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Information Ratio"</span>
     <span class="n">ir</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="n">ir_df</span> <span class="o">=</span> <span class="n">ir</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">ir_df</span><span class="p">])</span>
@@ -355,21 +355,21 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Tracking Error to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Tracking Error to the report dataframe."""</span>
     <span class="n">te_frame</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
-    <span class="n">te_frame</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">&quot;7D&quot;</span><span class="p">)</span>
+    <span class="n">te_frame</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">"7D"</span><span class="p">)</span>
     <span class="k">with</span> <span class="n">catch_warnings</span><span class="p">():</span>
-        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
+        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
         <span class="n">te</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="n">Series</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">te_frame</span><span class="o">.</span><span class="n">tracking_error_func</span><span class="p">()</span>
     <span class="k">if</span> <span class="n">te</span><span class="o">.</span><span class="n">hasnans</span><span class="p">:</span>
         <span class="n">te</span> <span class="o">=</span> <span class="n">Series</span><span class="p">(</span>
-            <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">]</span> <span class="o">*</span> <span class="n">te_frame</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
+            <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">""</span><span class="p">]</span> <span class="o">*</span> <span class="n">te_frame</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="n">te_frame</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"Tracking Error (weekly)"</span><span class="p">,</span>
         <span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">te</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
-        <span class="n">te</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Tracking Error (weekly)&quot;</span>
+        <span class="n">te</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Tracking Error (weekly)"</span>
     <span class="n">te_df</span> <span class="o">=</span> <span class="n">te</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">te_df</span><span class="p">])</span>
 
@@ -379,27 +379,27 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
     <span class="n">formats</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">DataFrame</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Capture Ratio to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Capture Ratio to the report dataframe."""</span>
     <span class="n">crm</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
-    <span class="n">crm</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">&quot;ME&quot;</span><span class="p">)</span>
+    <span class="n">crm</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">"ME"</span><span class="p">)</span>
     <span class="n">cru_save</span> <span class="o">=</span> <span class="n">Series</span><span class="p">(</span>
-        <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">]</span> <span class="o">*</span> <span class="n">crm</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
+        <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="s2">""</span><span class="p">]</span> <span class="o">*</span> <span class="n">crm</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
         <span class="n">index</span><span class="o">=</span><span class="n">crm</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-        <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Capture Ratio (monthly)&quot;</span><span class="p">,</span>
+        <span class="n">name</span><span class="o">=</span><span class="s2">"Capture Ratio (monthly)"</span><span class="p">,</span>
     <span class="p">)</span>
     <span class="k">with</span> <span class="n">catch_warnings</span><span class="p">():</span>
-        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>
+        <span class="n">simplefilter</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
         <span class="k">try</span><span class="p">:</span>
-            <span class="n">cru</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="n">Series</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">crm</span><span class="o">.</span><span class="n">capture_ratio_func</span><span class="p">(</span><span class="n">ratio</span><span class="o">=</span><span class="s2">&quot;both&quot;</span><span class="p">)</span>
+            <span class="n">cru</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="n">Series</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">crm</span><span class="o">.</span><span class="n">capture_ratio_func</span><span class="p">(</span><span class="n">ratio</span><span class="o">=</span><span class="s2">"both"</span><span class="p">)</span>
         <span class="k">except</span> <span class="ne">ZeroDivisionError</span> <span class="k">as</span> <span class="n">exc</span><span class="p">:</span>  <span class="c1"># pragma: no cover</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Capture ratio calculation error: </span><span class="si">{</span><span class="n">exc</span><span class="si">!s}</span><span class="s2">&quot;</span>  <span class="c1"># pragma: no cover</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Capture ratio calculation error: </span><span class="si">{</span><span class="n">exc</span><span class="si">!s}</span><span class="s2">"</span>  <span class="c1"># pragma: no cover</span>
             <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>  <span class="c1"># pragma: no cover</span>
             <span class="n">cru</span> <span class="o">=</span> <span class="n">cru_save</span>  <span class="c1"># pragma: no cover</span>
     <span class="k">if</span> <span class="n">cru</span><span class="o">.</span><span class="n">hasnans</span><span class="p">:</span>
         <span class="n">cru</span> <span class="o">=</span> <span class="n">cru_save</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">cru</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
-        <span class="n">cru</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Capture Ratio (monthly)&quot;</span>
+        <span class="n">cru</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Capture Ratio (monthly)"</span>
     <span class="n">cru_df</span> <span class="o">=</span> <span class="n">cru</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">cru_df</span><span class="p">]),</span> <span class="n">formats</span>
 
@@ -408,9 +408,9 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Index Beta to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Index Beta to the report dataframe."""</span>
     <span class="n">beta_frame</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
-    <span class="n">beta_frame</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">&quot;7D&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="s2">&quot;drop&quot;</span><span class="p">)</span>
+    <span class="n">beta_frame</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="s2">"7D"</span><span class="p">)</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="s2">"drop"</span><span class="p">)</span>
     <span class="n">beta_frame</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>
     <span class="n">betas</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span> <span class="o">|</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span>
         <span class="n">beta_frame</span><span class="o">.</span><span class="n">beta</span><span class="p">(</span>
@@ -419,11 +419,11 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
         <span class="p">)</span>
         <span class="k">for</span> <span class="n">bname</span> <span class="ow">in</span> <span class="n">beta_frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
     <span class="p">]</span>
-    <span class="n">betas</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
+    <span class="n">betas</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
     <span class="n">br</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span>
         <span class="n">data</span><span class="o">=</span><span class="n">betas</span><span class="p">,</span>
         <span class="n">index</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span>
-        <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">],</span>
+        <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"Index Beta (weekly)"</span><span class="p">],</span>
     <span class="p">)</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">br</span><span class="p">])</span>
 
@@ -432,26 +432,26 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add Year-to-Date and Month-to-Date to the report dataframe.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Add Year-to-Date and Month-to-Date to the report dataframe."""</span>
     <span class="n">this_year</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">last_idx</span><span class="o">.</span><span class="n">year</span>
     <span class="n">this_month</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">last_idx</span><span class="o">.</span><span class="n">month</span>
-    <span class="n">ytd</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">value_ret_calendar_period</span><span class="p">(</span><span class="n">year</span><span class="o">=</span><span class="n">this_year</span><span class="p">)</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">)</span>
-    <span class="n">ytd</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Year-to-Date&quot;</span>
+    <span class="n">ytd</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">value_ret_calendar_period</span><span class="p">(</span><span class="n">year</span><span class="o">=</span><span class="n">this_year</span><span class="p">)</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">)</span>
+    <span class="n">ytd</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Year-to-Date"</span>
     <span class="n">mtd</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">value_ret_calendar_period</span><span class="p">(</span><span class="n">year</span><span class="o">=</span><span class="n">this_year</span><span class="p">,</span> <span class="n">month</span><span class="o">=</span><span class="n">this_month</span><span class="p">)</span><span class="o">.</span><span class="n">map</span><span class="p">(</span>
-        <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">,</span>
+        <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">,</span>
     <span class="p">)</span>
-    <span class="n">mtd</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Month-to-Date&quot;</span>
+    <span class="n">mtd</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Month-to-Date"</span>
     <span class="n">ytd_df</span> <span class="o">=</span> <span class="n">ytd</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span><span class="o">.</span><span class="n">T</span>
     <span class="n">mtd_df</span> <span class="o">=</span> <span class="n">mtd</span><span class="o">.</span><span class="n">to_frame</span><span class="p">()</span><span class="o">.</span><span class="n">T</span>
     <span class="k">return</span> <span class="n">concat</span><span class="p">([</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">ytd_df</span><span class="p">,</span> <span class="n">mtd_df</span><span class="p">])</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_get_output_directory</span><span class="p">(</span><span class="n">directory</span><span class="p">:</span> <span class="n">Path</span> <span class="o">|</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Determine the output directory.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Determine the output directory."""</span>
     <span class="k">if</span> <span class="n">directory</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">Path</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span><span class="o">.</span><span class="n">resolve</span><span class="p">()</span>
-    <span class="k">if</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">&quot;Documents&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
-        <span class="k">return</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span> <span class="o">/</span> <span class="s2">&quot;Documents&quot;</span>
+    <span class="k">if</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span><span class="o">.</span><span class="n">joinpath</span><span class="p">(</span><span class="s2">"Documents"</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
+        <span class="k">return</span> <span class="n">Path</span><span class="o">.</span><span class="n">home</span><span class="p">()</span> <span class="o">/</span> <span class="s2">"Documents"</span>
     <span class="k">return</span> <span class="n">Path</span><span class="p">(</span><span class="n">stack</span><span class="p">()[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">filename</span><span class="p">)</span><span class="o">.</span><span class="n">parent</span>
 
 
@@ -460,26 +460,26 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">colorway</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
     <span class="n">item_count</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get line and bar layouts for plotly.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Get line and bar layouts for plotly."""</span>
     <span class="n">line_layout</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">layout_theme</span><span class="p">)</span>
     <span class="n">line_layout</span><span class="o">.</span><span class="n">update</span><span class="p">(</span>
         <span class="p">{</span>
-            <span class="s2">&quot;colorway&quot;</span><span class="p">:</span> <span class="n">colorway</span><span class="p">[:</span><span class="n">item_count</span><span class="p">]</span> <span class="k">if</span> <span class="n">colorway</span> <span class="k">else</span> <span class="kc">None</span><span class="p">,</span>
-            <span class="s2">&quot;margin&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;l&quot;</span><span class="p">:</span> <span class="mi">50</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">&quot;t&quot;</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">&quot;b&quot;</span><span class="p">:</span> <span class="mi">40</span><span class="p">},</span>
-            <span class="s2">&quot;xaxis&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;gridcolor&quot;</span><span class="p">:</span> <span class="s2">&quot;#EEEEEE&quot;</span><span class="p">,</span> <span class="s2">&quot;automargin&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">&quot;tickangle&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">45</span><span class="p">},</span>
-            <span class="s2">&quot;yaxis&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;tickformat&quot;</span><span class="p">:</span> <span class="s2">&quot;.2%&quot;</span><span class="p">,</span> <span class="s2">&quot;gridcolor&quot;</span><span class="p">:</span> <span class="s2">&quot;#EEEEEE&quot;</span><span class="p">,</span> <span class="s2">&quot;automargin&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
-            <span class="s2">&quot;showlegend&quot;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
+            <span class="s2">"colorway"</span><span class="p">:</span> <span class="n">colorway</span><span class="p">[:</span><span class="n">item_count</span><span class="p">]</span> <span class="k">if</span> <span class="n">colorway</span> <span class="k">else</span> <span class="kc">None</span><span class="p">,</span>
+            <span class="s2">"margin"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"l"</span><span class="p">:</span> <span class="mi">50</span><span class="p">,</span> <span class="s2">"r"</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">"b"</span><span class="p">:</span> <span class="mi">40</span><span class="p">},</span>
+            <span class="s2">"xaxis"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"gridcolor"</span><span class="p">:</span> <span class="s2">"#EEEEEE"</span><span class="p">,</span> <span class="s2">"automargin"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"tickangle"</span><span class="p">:</span> <span class="o">-</span><span class="mi">45</span><span class="p">},</span>
+            <span class="s2">"yaxis"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"tickformat"</span><span class="p">:</span> <span class="s2">".2%"</span><span class="p">,</span> <span class="s2">"gridcolor"</span><span class="p">:</span> <span class="s2">"#EEEEEE"</span><span class="p">,</span> <span class="s2">"automargin"</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
+            <span class="s2">"showlegend"</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
         <span class="p">},</span>
     <span class="p">)</span>
 
     <span class="n">bar_layout</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">layout_theme</span><span class="p">)</span>
     <span class="n">bar_layout</span><span class="o">.</span><span class="n">update</span><span class="p">(</span>
         <span class="p">{</span>
-            <span class="s2">&quot;barmode&quot;</span><span class="p">:</span> <span class="s2">&quot;group&quot;</span><span class="p">,</span>
-            <span class="s2">&quot;margin&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;l&quot;</span><span class="p">:</span> <span class="mi">50</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">&quot;t&quot;</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span> <span class="s2">&quot;b&quot;</span><span class="p">:</span> <span class="mi">80</span><span class="p">},</span>
-            <span class="s2">&quot;xaxis&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;gridcolor&quot;</span><span class="p">:</span> <span class="s2">&quot;#EEEEEE&quot;</span><span class="p">,</span> <span class="s2">&quot;automargin&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">&quot;tickangle&quot;</span><span class="p">:</span> <span class="o">-</span><span class="mi">45</span><span class="p">},</span>
-            <span class="s2">&quot;yaxis&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;tickformat&quot;</span><span class="p">:</span> <span class="s2">&quot;.2%&quot;</span><span class="p">,</span> <span class="s2">&quot;gridcolor&quot;</span><span class="p">:</span> <span class="s2">&quot;#EEEEEE&quot;</span><span class="p">,</span> <span class="s2">&quot;automargin&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
-            <span class="s2">&quot;showlegend&quot;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
+            <span class="s2">"barmode"</span><span class="p">:</span> <span class="s2">"group"</span><span class="p">,</span>
+            <span class="s2">"margin"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"l"</span><span class="p">:</span> <span class="mi">50</span><span class="p">,</span> <span class="s2">"r"</span><span class="p">:</span> <span class="mi">20</span><span class="p">,</span> <span class="s2">"t"</span><span class="p">:</span> <span class="mi">10</span><span class="p">,</span> <span class="s2">"b"</span><span class="p">:</span> <span class="mi">80</span><span class="p">},</span>
+            <span class="s2">"xaxis"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"gridcolor"</span><span class="p">:</span> <span class="s2">"#EEEEEE"</span><span class="p">,</span> <span class="s2">"automargin"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"tickangle"</span><span class="p">:</span> <span class="o">-</span><span class="mi">45</span><span class="p">},</span>
+            <span class="s2">"yaxis"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"tickformat"</span><span class="p">:</span> <span class="s2">".2%"</span><span class="p">,</span> <span class="s2">"gridcolor"</span><span class="p">:</span> <span class="s2">"#EEEEEE"</span><span class="p">,</span> <span class="s2">"automargin"</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
+            <span class="s2">"showlegend"</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
         <span class="p">},</span>
     <span class="p">)</span>
 
@@ -487,47 +487,47 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_get_logo_html</span><span class="p">(</span><span class="n">logo</span><span class="p">:</span> <span class="n">CaptorLogoType</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">add_logo</span><span class="p">:</span> <span class="nb">bool</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get logo HTML.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Get logo HTML."""</span>
     <span class="k">if</span> <span class="ow">not</span> <span class="n">add_logo</span><span class="p">:</span>
-        <span class="k">return</span> <span class="s2">&quot;&quot;</span>
+        <span class="k">return</span> <span class="s2">""</span>
     <span class="k">try</span><span class="p">:</span>
-        <span class="n">src</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;dict[str, Any]&quot;</span><span class="p">,</span> <span class="n">logo</span><span class="p">)</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;source&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">)</span>
+        <span class="n">src</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"dict[str, Any]"</span><span class="p">,</span> <span class="n">logo</span><span class="p">)</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"source"</span><span class="p">,</span> <span class="s2">""</span><span class="p">)</span>
     <span class="k">except</span> <span class="p">(</span><span class="ne">KeyError</span><span class="p">,</span> <span class="ne">AttributeError</span><span class="p">,</span> <span class="ne">TypeError</span><span class="p">):</span>
-        <span class="n">src</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
+        <span class="n">src</span> <span class="o">=</span> <span class="s2">""</span>
     <span class="k">if</span> <span class="n">src</span><span class="p">:</span>
-        <span class="k">return</span> <span class="sa">f</span><span class="s1">&#39;&lt;img src=&quot;</span><span class="si">{</span><span class="n">src</span><span class="si">}</span><span class="s1">&quot; alt=&quot;Captor&quot; style=&quot;height:68px;&quot; /&gt;&#39;</span>
-    <span class="k">return</span> <span class="s2">&quot;CAPTOR&quot;</span>
+        <span class="k">return</span> <span class="sa">f</span><span class="s1">'&lt;img src="</span><span class="si">{</span><span class="n">src</span><span class="si">}</span><span class="s1">" alt="Captor" style="height:68px;" /&gt;'</span>
+    <span class="k">return</span> <span class="s2">"CAPTOR"</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_get_legend_html</span><span class="p">(</span><span class="n">line_traces</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Scatter</span><span class="p">],</span> <span class="n">colorway</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate HTML for the legend at the bottom of the page.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Generate HTML for the legend at the bottom of the page."""</span>
     <span class="n">legend_items</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="n">color_cycle</span> <span class="o">=</span> <span class="n">cycle</span><span class="p">(</span><span class="n">colorway</span> <span class="ow">or</span> <span class="p">[</span><span class="s2">&quot;#66725B&quot;</span><span class="p">])</span>
+    <span class="n">color_cycle</span> <span class="o">=</span> <span class="n">cycle</span><span class="p">(</span><span class="n">colorway</span> <span class="ow">or</span> <span class="p">[</span><span class="s2">"#66725B"</span><span class="p">])</span>
     <span class="k">for</span> <span class="n">trace</span> <span class="ow">in</span> <span class="n">line_traces</span><span class="p">:</span>
-        <span class="n">name</span> <span class="o">=</span> <span class="n">trace</span><span class="o">.</span><span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;&quot;</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">trace</span><span class="o">.</span><span class="n">name</span> <span class="ow">or</span> <span class="s2">""</span>
         <span class="n">color</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">color_cycle</span><span class="p">)</span>
         <span class="n">legend_items</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
-            <span class="sa">f</span><span class="s1">&#39;&lt;div class=&quot;legend-item&quot;&gt;&#39;</span>
-            <span class="sa">f</span><span class="s1">&#39;&lt;div class=&quot;legend-color&quot; style=&quot;background-color:</span><span class="si">{</span><span class="n">color</span><span class="si">}</span><span class="s1">;&quot;&gt;&lt;/div&gt;&#39;</span>
-            <span class="sa">f</span><span class="s2">&quot;&lt;span&gt;</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">&lt;/span&gt;&quot;</span>
-            <span class="sa">f</span><span class="s2">&quot;&lt;/div&gt;&quot;</span><span class="p">,</span>
+            <span class="sa">f</span><span class="s1">'&lt;div class="legend-item"&gt;'</span>
+            <span class="sa">f</span><span class="s1">'&lt;div class="legend-color" style="background-color:</span><span class="si">{</span><span class="n">color</span><span class="si">}</span><span class="s1">;"&gt;&lt;/div&gt;'</span>
+            <span class="sa">f</span><span class="s2">"&lt;span&gt;</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">&lt;/span&gt;"</span>
+            <span class="sa">f</span><span class="s2">"&lt;/div&gt;"</span><span class="p">,</span>
         <span class="p">)</span>
     <span class="k">if</span> <span class="n">legend_items</span><span class="p">:</span>
-        <span class="k">return</span> <span class="sa">f</span><span class="s1">&#39;&lt;div class=&quot;legend-container&quot;&gt;</span><span class="si">{</span><span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">legend_items</span><span class="p">)</span><span class="si">}</span><span class="s1">&lt;/div&gt;&#39;</span>
-    <span class="k">return</span> <span class="s2">&quot;&quot;</span>
+        <span class="k">return</span> <span class="sa">f</span><span class="s1">'&lt;div class="legend-container"&gt;</span><span class="si">{</span><span class="s2">""</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">legend_items</span><span class="p">)</span><span class="si">}</span><span class="s1">&lt;/div&gt;'</span>
+    <span class="k">return</span> <span class="s2">""</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_get_css</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get CSS styles for the HTML report.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Get CSS styles for the HTML report."""</span>
     <span class="n">base_css</span> <span class="o">=</span> <span class="n">_get_base_css</span><span class="p">()</span>
     <span class="k">return</span> <span class="p">(</span>
         <span class="n">base_css</span>
-        <span class="o">+</span> <span class="s2">&quot;&quot;&quot;</span>
+        <span class="o">+</span> <span class="s2">"""</span>
 <span class="s2">    .header{display:grid;grid-template-columns:140px 1fr 140px;gap:12px;</span>
 <span class="s2">    align-items:start;}</span>
 <span class="s2">    h1{margin:0;text-align:center;font-size:45px;font-weight:800;}</span>
 <span class="s2">    .layout{display:grid;grid-template-columns:1.2fr .9fr;</span>
-<span class="s2">    grid-template-areas:&quot;charts table&quot;;gap:22px;align-items:start;margin-top:12px;}</span>
+<span class="s2">    grid-template-areas:"charts table";gap:22px;align-items:start;margin-top:12px;}</span>
 <span class="s2">    .charts{grid-area:charts;display:grid;grid-template-rows:auto auto;gap:18px;}</span>
 <span class="s2">    .table{grid-area:table;}</span>
 <span class="s2">    .plot{width:100%;height:380px;}</span>
@@ -536,7 +536,7 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
 <span class="s2">      .page{padding:24px;padding-bottom:24px;}</span>
 <span class="s2">      .header{grid-template-columns:120px 1fr;}</span>
 <span class="s2">      h1{font-size:36px;}</span>
-<span class="s2">      .layout{grid-template-columns:1fr;grid-template-areas:&quot;table&quot; &quot;charts&quot;;gap:16px;}</span>
+<span class="s2">      .layout{grid-template-columns:1fr;grid-template-areas:"table" "charts";gap:16px;}</span>
 <span class="s2">      .plot{height:380px;}</span>
 <span class="s2">      .plot.bar{height:300px;}</span>
 <span class="s2">      table.metrics{table-layout:fixed;width:auto;}</span>
@@ -563,7 +563,7 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
 <span class="s2">    @media (min-width:981px){</span>
 <span class="s2">      html,body{overflow-y:auto;}</span>
 <span class="s2">    }</span>
-<span class="s2">    &quot;&quot;&quot;</span>
+<span class="s2">    """</span>
     <span class="p">)</span>
 
 
@@ -573,14 +573,14 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Write HTML file and optionally open it.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Write HTML file and optionally open it."""</span>
     <span class="n">plotfile</span><span class="o">.</span><span class="n">parent</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">parents</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-    <span class="n">plotfile</span><span class="o">.</span><span class="n">write_text</span><span class="p">(</span><span class="n">html</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span>
+    <span class="n">plotfile</span><span class="o">.</span><span class="n">write_text</span><span class="p">(</span><span class="n">html</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span>
     <span class="k">if</span> <span class="n">auto_open</span><span class="p">:</span>
         <span class="k">try</span><span class="p">:</span>
             <span class="n">webbrowser_open</span><span class="p">(</span><span class="n">plotfile</span><span class="o">.</span><span class="n">as_uri</span><span class="p">())</span>
         <span class="k">except</span> <span class="ne">OSError</span> <span class="k">as</span> <span class="n">exc</span><span class="p">:</span>
-            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s2">&quot;Failed to open browser: </span><span class="si">%s</span><span class="s2">&quot;</span><span class="p">,</span> <span class="n">exc</span><span class="p">)</span>
+            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s2">"Failed to open browser: </span><span class="si">%s</span><span class="s2">"</span><span class="p">,</span> <span class="n">exc</span><span class="p">)</span>
     <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="n">plotfile</span><span class="p">)</span>
 
 
@@ -594,63 +594,63 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">bar_payload</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span>
     <span class="n">legend_html</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate the HTML string.&quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="sa">f</span><span class="s2">&quot;&quot;&quot;&lt;!doctype html&gt;</span>
-<span class="s2">&lt;html lang=&quot;sv&quot;&gt;</span>
+<span class="w">    </span><span class="sd">"""Generate the HTML string."""</span>
+    <span class="k">return</span> <span class="sa">f</span><span class="s2">"""&lt;!doctype html&gt;</span>
+<span class="s2">&lt;html lang="sv"&gt;</span>
 <span class="s2">&lt;head&gt;</span>
-<span class="s2">&lt;meta charset=&quot;utf-8&quot; /&gt;</span>
-<span class="s2">&lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,initial-scale=1&quot; /&gt;</span>
-<span class="s2">&lt;title&gt;</span><span class="si">{</span><span class="n">title</span><span class="w"> </span><span class="ow">or</span><span class="w"> </span><span class="s2">&quot;&quot;</span><span class="si">}</span><span class="s2">&lt;/title&gt;</span>
+<span class="s2">&lt;meta charset="utf-8" /&gt;</span>
+<span class="s2">&lt;meta name="viewport" content="width=device-width,initial-scale=1" /&gt;</span>
+<span class="s2">&lt;title&gt;</span><span class="si">{</span><span class="n">title</span><span class="w"> </span><span class="ow">or</span><span class="w"> </span><span class="s2">""</span><span class="si">}</span><span class="s2">&lt;/title&gt;</span>
 <span class="s2">&lt;style&gt;</span><span class="si">{</span><span class="n">css</span><span class="si">}</span><span class="s2">&lt;/style&gt;</span>
 <span class="si">{</span><span class="n">plotly_script</span><span class="si">}</span>
 <span class="s2">&lt;/head&gt;</span>
 <span class="s2">&lt;body&gt;</span>
-<span class="s2">&lt;div class=&quot;page&quot;&gt;</span>
-<span class="s2">  &lt;div class=&quot;header&quot;&gt;</span>
+<span class="s2">&lt;div class="page"&gt;</span>
+<span class="s2">  &lt;div class="header"&gt;</span>
 <span class="s2">    &lt;div&gt;</span><span class="si">{</span><span class="n">logo_html</span><span class="si">}</span><span class="s2">&lt;/div&gt;</span>
-<span class="s2">    &lt;div&gt;&lt;h1&gt;</span><span class="si">{</span><span class="n">title</span><span class="w"> </span><span class="ow">or</span><span class="w"> </span><span class="s2">&quot;&quot;</span><span class="si">}</span><span class="s2">&lt;/h1&gt;&lt;/div&gt;</span>
+<span class="s2">    &lt;div&gt;&lt;h1&gt;</span><span class="si">{</span><span class="n">title</span><span class="w"> </span><span class="ow">or</span><span class="w"> </span><span class="s2">""</span><span class="si">}</span><span class="s2">&lt;/h1&gt;&lt;/div&gt;</span>
 <span class="s2">    &lt;div&gt;&lt;/div&gt;</span>
 <span class="s2">  &lt;/div&gt;</span>
-<span class="s2">  &lt;div class=&quot;layout&quot;&gt;</span>
-<span class="s2">    &lt;div class=&quot;charts&quot;&gt;</span>
-<span class="s2">      &lt;div id=&quot;lineplot&quot; class=&quot;plot&quot;&gt;&lt;/div&gt;</span>
-<span class="s2">      &lt;div id=&quot;barplot&quot; class=&quot;plot bar&quot;&gt;&lt;/div&gt;</span>
+<span class="s2">  &lt;div class="layout"&gt;</span>
+<span class="s2">    &lt;div class="charts"&gt;</span>
+<span class="s2">      &lt;div id="lineplot" class="plot"&gt;&lt;/div&gt;</span>
+<span class="s2">      &lt;div id="barplot" class="plot bar"&gt;&lt;/div&gt;</span>
 <span class="s2">    &lt;/div&gt;</span>
-<span class="s2">    &lt;div class=&quot;table&quot;&gt;</span><span class="si">{</span><span class="n">table_html</span><span class="si">}</span><span class="s2">&lt;/div&gt;</span>
+<span class="s2">    &lt;div class="table"&gt;</span><span class="si">{</span><span class="n">table_html</span><span class="si">}</span><span class="s2">&lt;/div&gt;</span>
 <span class="s2">  &lt;/div&gt;</span>
 <span class="s2">  </span><span class="si">{</span><span class="n">legend_html</span><span class="si">}</span>
 <span class="s2">&lt;/div&gt;</span>
 <span class="s2">&lt;script&gt;</span>
 <span class="s2">const line = </span><span class="si">{</span><span class="n">_dumps_plotly</span><span class="p">(</span><span class="n">line_payload</span><span class="p">)</span><span class="si">}</span><span class="s2">;</span>
 <span class="s2">const bar = </span><span class="si">{</span><span class="n">_dumps_plotly</span><span class="p">(</span><span class="n">bar_payload</span><span class="p">)</span><span class="si">}</span><span class="s2">;</span>
-<span class="s2">Plotly.newPlot(&quot;lineplot&quot;, line.data, line.layout, line.config);</span>
-<span class="s2">Plotly.newPlot(&quot;barplot&quot;, bar.data, bar.layout, bar.config);</span>
-<span class="s2">window.addEventListener(&quot;resize&quot;, () =&gt; </span><span class="se">{{</span>
-<span class="s2">  Plotly.Plots.resize(&quot;lineplot&quot;);</span>
-<span class="s2">  Plotly.Plots.resize(&quot;barplot&quot;);</span>
+<span class="s2">Plotly.newPlot("lineplot", line.data, line.layout, line.config);</span>
+<span class="s2">Plotly.newPlot("barplot", bar.data, bar.layout, bar.config);</span>
+<span class="s2">window.addEventListener("resize", () =&gt; </span><span class="se">{{</span>
+<span class="s2">  Plotly.Plots.resize("lineplot");</span>
+<span class="s2">  Plotly.Plots.resize("barplot");</span>
 <span class="se">}}</span><span class="s2">);</span>
 <span class="s2">&lt;/script&gt;</span>
 <span class="s2">&lt;/body&gt;</span>
 <span class="s2">&lt;/html&gt;</span>
-<span class="s2">&quot;&quot;&quot;</span>
+<span class="s2">"""</span>
 
 
 <div class="viewcode-block" id="report_html">
 <a class="viewcode-back" href="../../api/report.html#openseries.report_html">[docs]</a>
 <span class="k">def</span><span class="w"> </span><span class="nf">report_html</span><span class="p">(</span>
     <span class="n">data</span><span class="p">:</span> <span class="n">OpenFrame</span><span class="p">,</span>
-    <span class="n">bar_freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">&quot;BYE&quot;</span><span class="p">,</span>
+    <span class="n">bar_freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">"BYE"</span><span class="p">,</span>
     <span class="n">filename</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">title</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">directory</span><span class="p">:</span> <span class="n">Path</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">output_type</span><span class="p">:</span> <span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="s2">&quot;file&quot;</span><span class="p">,</span>
-    <span class="n">include_plotlyjs</span><span class="p">:</span> <span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="s2">&quot;cdn&quot;</span><span class="p">,</span>
+    <span class="n">output_type</span><span class="p">:</span> <span class="n">LiteralPlotlyOutput</span> <span class="o">=</span> <span class="s2">"file"</span><span class="p">,</span>
+    <span class="n">include_plotlyjs</span><span class="p">:</span> <span class="n">LiteralPlotlyJSlib</span> <span class="o">=</span> <span class="s2">"cdn"</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="n">add_logo</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="n">vertical_legend</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">Figure</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Generate a responsive HTML report page with line and bar plots and a table.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Generate a responsive HTML report page with line and bar plots and a table."""</span>
     <span class="n">copied</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
     <span class="n">copied</span><span class="o">.</span><span class="n">trunc_frame</span><span class="p">()</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">()</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>
 
@@ -662,7 +662,7 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">bar_traces</span> <span class="o">=</span> <span class="n">_create_bar_traces</span><span class="p">(</span><span class="n">copied</span><span class="p">,</span> <span class="n">bar_freq</span><span class="p">)</span>
 
     <span class="n">rpt_df</span> <span class="o">=</span> <span class="n">copied</span><span class="o">.</span><span class="n">all_properties</span><span class="p">(</span>
-        <span class="n">properties</span><span class="o">=</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;list[LiteralFrameProps]&quot;</span><span class="p">,</span> <span class="n">properties</span><span class="p">),</span>
+        <span class="n">properties</span><span class="o">=</span><span class="n">cast</span><span class="p">(</span><span class="s2">"list[LiteralFrameProps]"</span><span class="p">,</span> <span class="n">properties</span><span class="p">),</span>
     <span class="p">)</span>
     <span class="n">rpt_df</span> <span class="o">=</span> <span class="n">_add_jensen_alpha</span><span class="p">(</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">copied</span><span class="p">)</span>
     <span class="n">rpt_df</span> <span class="o">=</span> <span class="n">_add_information_ratio</span><span class="p">(</span><span class="n">rpt_df</span><span class="p">,</span> <span class="n">copied</span><span class="p">)</span>
@@ -677,64 +677,64 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
     <span class="n">rpt_df</span> <span class="o">=</span> <span class="n">rpt_df</span><span class="o">.</span><span class="n">reindex</span><span class="p">(</span><span class="n">labels_final</span><span class="p">)</span>
 
     <span class="n">format_map</span> <span class="o">=</span> <span class="p">{</span>
-        <span class="s2">&quot;Return (CAGR)&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Return (simple)&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Year-to-Date&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Month-to-Date&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Volatility&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Sharpe Ratio&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Sortino Ratio&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Jensen&#39;s Alpha&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Information Ratio&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Tracking Error (weekly)&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Index Beta (weekly)&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Capture Ratio (monthly)&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Worst Month&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Worst Day&quot;</span><span class="p">:</span> <span class="s2">&quot;</span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Comparison Start&quot;</span><span class="p">:</span> <span class="s2">&quot;{:%Y-%m-</span><span class="si">%d</span><span class="s2">}&quot;</span><span class="p">,</span>
-        <span class="s2">&quot;Comparison End&quot;</span><span class="p">:</span> <span class="s2">&quot;{:%Y-%m-</span><span class="si">%d</span><span class="s2">}&quot;</span><span class="p">,</span>
+        <span class="s2">"Return (CAGR)"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Return (simple)"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Year-to-Date"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Month-to-Date"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Volatility"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Sharpe Ratio"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Sortino Ratio"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Jensen's Alpha"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Information Ratio"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Tracking Error (weekly)"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Index Beta (weekly)"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Capture Ratio (monthly)"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Worst Month"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Worst Day"</span><span class="p">:</span> <span class="s2">"</span><span class="si">{:.2%}</span><span class="s2">"</span><span class="p">,</span>
+        <span class="s2">"Comparison Start"</span><span class="p">:</span> <span class="s2">"{:%Y-%m-</span><span class="si">%d</span><span class="s2">}"</span><span class="p">,</span>
+        <span class="s2">"Comparison End"</span><span class="p">:</span> <span class="s2">"{:%Y-%m-</span><span class="si">%d</span><span class="s2">}"</span><span class="p">,</span>
     <span class="p">}</span>
-    <span class="n">formats</span> <span class="o">=</span> <span class="p">[</span><span class="n">format_map</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="s2">&quot;</span><span class="si">{:.2f}</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">labels_final</span><span class="p">]</span>
+    <span class="n">formats</span> <span class="o">=</span> <span class="p">[</span><span class="n">format_map</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="s2">"</span><span class="si">{:.2f}</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">labels_final</span><span class="p">]</span>
 
     <span class="k">for</span> <span class="n">item</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">rpt_df</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">formats</span><span class="p">,</span> <span class="n">strict</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
         <span class="n">rpt_df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">item</span><span class="p">]</span> <span class="o">=</span> <span class="n">rpt_df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">item</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>
             <span class="k">lambda</span> <span class="n">x</span><span class="p">,</span> <span class="n">fmt</span><span class="o">=</span><span class="n">f</span><span class="p">:</span> <span class="p">(</span>
-                <span class="s2">&quot;&quot;</span>
+                <span class="s2">""</span>
                 <span class="k">if</span> <span class="p">(</span>
                     <span class="n">x</span> <span class="ow">is</span> <span class="kc">None</span>
                     <span class="ow">or</span> <span class="p">(</span><span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="n">isna</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
-                    <span class="ow">or</span> <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="n">x</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="ow">in</span> <span class="p">(</span><span class="s2">&quot;nan&quot;</span><span class="p">,</span> <span class="s2">&quot;nan%&quot;</span><span class="p">,</span> <span class="s2">&quot;&quot;</span><span class="p">))</span>
+                    <span class="ow">or</span> <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="n">x</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="ow">in</span> <span class="p">(</span><span class="s2">"nan"</span><span class="p">,</span> <span class="s2">"nan%"</span><span class="p">,</span> <span class="s2">""</span><span class="p">))</span>
                 <span class="p">)</span>
                 <span class="k">else</span> <span class="p">(</span>
                     <span class="nb">str</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
                     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
                     <span class="k">else</span> <span class="p">(</span>
-                        <span class="n">Timestamp</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span>
-                        <span class="k">if</span> <span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span> <span class="ow">in</span> <span class="n">fmt</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
+                        <span class="n">Timestamp</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span>
+                        <span class="k">if</span> <span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span> <span class="ow">in</span> <span class="n">fmt</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
                         <span class="k">else</span> <span class="n">fmt</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
                     <span class="p">)</span>
                 <span class="p">)</span>
             <span class="p">),</span>
         <span class="p">)</span>
 
-    <span class="n">rpt_df</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">([</span><span class="sa">f</span><span class="s2">&quot;&lt;b&gt;</span><span class="si">{</span><span class="n">x</span><span class="si">}</span><span class="s2">&lt;/b&gt;&quot;</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">rpt_df</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
+    <span class="n">rpt_df</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">Index</span><span class="p">([</span><span class="sa">f</span><span class="s2">"&lt;b&gt;</span><span class="si">{</span><span class="n">x</span><span class="si">}</span><span class="s2">&lt;/b&gt;"</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">rpt_df</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
     <span class="n">rpt_df</span> <span class="o">=</span> <span class="n">rpt_df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
 
-    <span class="n">colmns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="o">*</span><span class="n">copied</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">]</span>
+    <span class="n">colmns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">""</span><span class="p">,</span> <span class="o">*</span><span class="n">copied</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">]</span>
     <span class="n">rpt_df</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">colmns</span>
     <span class="n">table_html</span> <span class="o">=</span> <span class="n">_metrics_table_html</span><span class="p">(</span><span class="n">rpt_df</span><span class="p">)</span>
 
     <span class="n">dirpath</span> <span class="o">=</span> <span class="n">_get_output_directory</span><span class="p">(</span><span class="n">directory</span><span class="o">=</span><span class="n">directory</span><span class="p">)</span>
 
     <span class="k">if</span> <span class="ow">not</span> <span class="n">filename</span><span class="p">:</span>
-        <span class="n">filename</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">choice</span><span class="p">(</span><span class="n">ascii_letters</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">6</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot;.html&quot;</span>
+        <span class="n">filename</span> <span class="o">=</span> <span class="s2">""</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">choice</span><span class="p">(</span><span class="n">ascii_letters</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">6</span><span class="p">))</span> <span class="o">+</span> <span class="s2">".html"</span>
 
     <span class="n">plotfile</span> <span class="o">=</span> <span class="n">dirpath</span> <span class="o">/</span> <span class="n">filename</span>
 
     <span class="n">fig_theme</span><span class="p">,</span> <span class="n">logo</span> <span class="o">=</span> <span class="n">load_plotly_dict</span><span class="p">()</span>
-    <span class="n">layout_theme</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;dict[str, Any]&quot;</span><span class="p">,</span> <span class="n">fig_theme</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;layout&quot;</span><span class="p">,</span> <span class="p">{}))</span>
-    <span class="n">colorway</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;dict[str, list[str]]&quot;</span><span class="p">,</span> <span class="n">layout_theme</span><span class="p">)</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
-        <span class="s2">&quot;colorway&quot;</span><span class="p">,</span> <span class="p">[]</span>
+    <span class="n">layout_theme</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"dict[str, Any]"</span><span class="p">,</span> <span class="n">fig_theme</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"layout"</span><span class="p">,</span> <span class="p">{}))</span>
+    <span class="n">colorway</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"dict[str, list[str]]"</span><span class="p">,</span> <span class="n">layout_theme</span><span class="p">)</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
+        <span class="s2">"colorway"</span><span class="p">,</span> <span class="p">[]</span>
     <span class="p">)</span>
 
     <span class="n">line_layout</span><span class="p">,</span> <span class="n">bar_layout</span> <span class="o">=</span> <span class="n">_get_plotly_layouts</span><span class="p">(</span>
@@ -743,26 +743,26 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
         <span class="n">item_count</span><span class="o">=</span><span class="n">copied</span><span class="o">.</span><span class="n">item_count</span><span class="p">,</span>
     <span class="p">)</span>
 
-    <span class="n">config</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;dict[str, Any]&quot;</span><span class="p">,</span> <span class="n">fig_theme</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;config&quot;</span><span class="p">,</span> <span class="p">{}))</span> <span class="ow">or</span> <span class="p">{}</span>
-    <span class="n">config</span> <span class="o">=</span> <span class="p">{</span><span class="o">**</span><span class="n">config</span><span class="p">,</span> <span class="s2">&quot;responsive&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">&quot;displayModeBar&quot;</span><span class="p">:</span> <span class="kc">False</span><span class="p">}</span>
+    <span class="n">config</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"dict[str, Any]"</span><span class="p">,</span> <span class="n">fig_theme</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"config"</span><span class="p">,</span> <span class="p">{}))</span> <span class="ow">or</span> <span class="p">{}</span>
+    <span class="n">config</span> <span class="o">=</span> <span class="p">{</span><span class="o">**</span><span class="n">config</span><span class="p">,</span> <span class="s2">"responsive"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"displayModeBar"</span><span class="p">:</span> <span class="kc">False</span><span class="p">}</span>
 
     <span class="n">plotly_script</span> <span class="o">=</span> <span class="n">_get_plotly_script</span><span class="p">(</span><span class="n">include_plotlyjs</span><span class="o">=</span><span class="n">include_plotlyjs</span><span class="p">)</span>
     <span class="n">logo_html</span> <span class="o">=</span> <span class="n">_get_logo_html</span><span class="p">(</span><span class="n">logo</span><span class="o">=</span><span class="n">logo</span><span class="p">,</span> <span class="n">add_logo</span><span class="o">=</span><span class="n">add_logo</span><span class="p">)</span>
     <span class="n">css</span> <span class="o">=</span> <span class="n">_get_css</span><span class="p">()</span>
 
     <span class="n">line_payload</span> <span class="o">=</span> <span class="p">{</span>
-        <span class="s2">&quot;data&quot;</span><span class="p">:</span> <span class="p">[</span><span class="n">t</span><span class="o">.</span><span class="n">to_plotly_json</span><span class="p">()</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">line_traces</span><span class="p">],</span>
-        <span class="s2">&quot;layout&quot;</span><span class="p">:</span> <span class="n">line_layout</span><span class="p">,</span>
-        <span class="s2">&quot;config&quot;</span><span class="p">:</span> <span class="n">config</span><span class="p">,</span>
+        <span class="s2">"data"</span><span class="p">:</span> <span class="p">[</span><span class="n">t</span><span class="o">.</span><span class="n">to_plotly_json</span><span class="p">()</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">line_traces</span><span class="p">],</span>
+        <span class="s2">"layout"</span><span class="p">:</span> <span class="n">line_layout</span><span class="p">,</span>
+        <span class="s2">"config"</span><span class="p">:</span> <span class="n">config</span><span class="p">,</span>
     <span class="p">}</span>
     <span class="n">bar_payload</span> <span class="o">=</span> <span class="p">{</span>
-        <span class="s2">&quot;data&quot;</span><span class="p">:</span> <span class="p">[</span><span class="n">t</span><span class="o">.</span><span class="n">to_plotly_json</span><span class="p">()</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">bar_traces</span><span class="p">],</span>
-        <span class="s2">&quot;layout&quot;</span><span class="p">:</span> <span class="n">bar_layout</span><span class="p">,</span>
-        <span class="s2">&quot;config&quot;</span><span class="p">:</span> <span class="n">config</span><span class="p">,</span>
+        <span class="s2">"data"</span><span class="p">:</span> <span class="p">[</span><span class="n">t</span><span class="o">.</span><span class="n">to_plotly_json</span><span class="p">()</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">bar_traces</span><span class="p">],</span>
+        <span class="s2">"layout"</span><span class="p">:</span> <span class="n">bar_layout</span><span class="p">,</span>
+        <span class="s2">"config"</span><span class="p">:</span> <span class="n">config</span><span class="p">,</span>
     <span class="p">}</span>
 
     <span class="k">if</span> <span class="ow">not</span> <span class="n">vertical_legend</span><span class="p">:</span>
-        <span class="n">logger</span><span class="o">.</span><span class="n">debug</span><span class="p">(</span><span class="s2">&quot;Horizontal legend layout requested.&quot;</span><span class="p">)</span>
+        <span class="n">logger</span><span class="o">.</span><span class="n">debug</span><span class="p">(</span><span class="s2">"Horizontal legend layout requested."</span><span class="p">)</span>
     <span class="n">legend_html</span> <span class="o">=</span> <span class="n">_get_legend_html</span><span class="p">(</span><span class="n">line_traces</span><span class="o">=</span><span class="n">line_traces</span><span class="p">,</span> <span class="n">colorway</span><span class="o">=</span><span class="n">colorway</span><span class="p">)</span>
 
     <span class="n">html</span> <span class="o">=</span> <span class="n">_generate_html</span><span class="p">(</span>
@@ -776,7 +776,7 @@ <h1>Source code for openseries.report</h1><div class="highlight"><pre>
         <span class="n">legend_html</span><span class="o">=</span><span class="n">legend_html</span><span class="p">,</span>
     <span class="p">)</span>
 
-    <span class="k">if</span> <span class="n">output_type</span> <span class="o">==</span> <span class="s2">&quot;file&quot;</span><span class="p">:</span>
+    <span class="k">if</span> <span class="n">output_type</span> <span class="o">==</span> <span class="s2">"file"</span><span class="p">:</span>
         <span class="n">output</span> <span class="o">=</span> <span class="n">_write_html_file</span><span class="p">(</span><span class="n">plotfile</span><span class="o">=</span><span class="n">plotfile</span><span class="p">,</span> <span class="n">html</span><span class="o">=</span><span class="n">html</span><span class="p">,</span> <span class="n">auto_open</span><span class="o">=</span><span class="n">auto_open</span><span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="n">output</span> <span class="o">=</span> <span class="n">html</span>
diff --git a/docs/build/html/_modules/openseries/series.html b/docs/build/html/_modules/openseries/series.html
index dffa6883..6b070b91 100644
--- a/docs/build/html/_modules/openseries/series.html
+++ b/docs/build/html/_modules/openseries/series.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.series</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;The OpenTimeSeries class.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""The OpenTimeSeries class."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -172,15 +172,15 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="n">logger</span> <span class="o">=</span> <span class="n">getLogger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;OpenTimeSeries&quot;</span><span class="p">,</span> <span class="s2">&quot;timeseries_chain&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"OpenTimeSeries"</span><span class="p">,</span> <span class="s2">"timeseries_chain"</span><span class="p">]</span>
 
-<span class="n">TypeOpenTimeSeries</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">&quot;TypeOpenTimeSeries&quot;</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="s2">&quot;OpenTimeSeries&quot;</span><span class="p">)</span>
+<span class="n">TypeOpenTimeSeries</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">"TypeOpenTimeSeries"</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="s2">"OpenTimeSeries"</span><span class="p">)</span>
 
 
 <div class="viewcode-block" id="OpenTimeSeries">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">OpenTimeSeries</span><span class="p">(</span><span class="n">_CommonModel</span><span class="p">[</span><span class="nb">float</span><span class="p">]):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;OpenTimeSeries objects are at the core of the openseries package.</span>
+<span class="w">    </span><span class="sd">"""OpenTimeSeries objects are at the core of the openseries package.</span>
 
 <span class="sd">    The intended use is to allow analyses of financial timeseries.</span>
 <span class="sd">    It is only intended for daily or less frequent data samples.</span>
@@ -199,15 +199,15 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">        tsdf: Pandas object holding dates and values that can be altered via</span>
 <span class="sd">            methods.</span>
 <span class="sd">        currency: ISO 4217 currency code of the timeseries.</span>
-<span class="sd">        domestic: ISO 4217 currency code of the user&#39;s home currency.</span>
-<span class="sd">            Defaults to &quot;SEK&quot;.</span>
+<span class="sd">        domestic: ISO 4217 currency code of the user's home currency.</span>
+<span class="sd">            Defaults to "SEK".</span>
 <span class="sd">        countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">            Defaults to &quot;SE&quot;.</span>
+<span class="sd">            Defaults to "SE".</span>
 <span class="sd">        markets: (List of) markets code(s) supported by exchange_calendars.</span>
 <span class="sd">            Optional.</span>
 <span class="sd">        isin: ISO 6166 identifier code of the associated instrument. Optional.</span>
 <span class="sd">        label: Placeholder for a name of the timeseries. Optional.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
 
     <span class="n">timeseries_id</span><span class="p">:</span> <span class="nb">str</span>
     <span class="n">instrument_id</span><span class="p">:</span> <span class="nb">str</span>
@@ -218,70 +218,70 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
     <span class="n">local_ccy</span><span class="p">:</span> <span class="nb">bool</span>
     <span class="n">tsdf</span><span class="p">:</span> <span class="n">DataFrame</span>
     <span class="n">currency</span><span class="p">:</span> <span class="n">CurrencyStringType</span>
-    <span class="n">domestic</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">&quot;SEK&quot;</span>
-    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span>
+    <span class="n">domestic</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">"SEK"</span>
+    <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span>
     <span class="n">isin</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="n">label</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 
-    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">&quot;domestic&quot;</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;before&quot;</span><span class="p">)</span>
+    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">"domestic"</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"before"</span><span class="p">)</span>
     <span class="nd">@classmethod</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_validate_domestic</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">CurrencyStringType</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">CurrencyStringType</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Pydantic validator to ensure domestic field is validated.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Pydantic validator to ensure domestic field is validated."""</span>
         <span class="n">Currency</span><span class="p">(</span><span class="n">ccy</span><span class="o">=</span><span class="n">value</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">value</span>
 
-    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">&quot;countries&quot;</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;before&quot;</span><span class="p">)</span>
+    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">"countries"</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"before"</span><span class="p">)</span>
     <span class="nd">@classmethod</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_validate_countries</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">CountriesType</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">CountriesType</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Pydantic validator to ensure countries field is validated.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Pydantic validator to ensure countries field is validated."""</span>
         <span class="n">Countries</span><span class="p">(</span><span class="n">countryinput</span><span class="o">=</span><span class="n">value</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">value</span>
 
-    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">&quot;markets&quot;</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;before&quot;</span><span class="p">)</span>
+    <span class="nd">@field_validator</span><span class="p">(</span><span class="s2">"markets"</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"before"</span><span class="p">)</span>
     <span class="nd">@classmethod</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_validate_markets</span><span class="p">(</span>
         <span class="bp">cls</span><span class="p">,</span>
         <span class="n">value</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Pydantic validator to ensure markets field is validated.</span>
+<span class="w">        </span><span class="sd">"""Pydantic validator to ensure markets field is validated.</span>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            MarketsNotStringNorListStrError: If ``markets`` is neither a string</span>
 <span class="sd">                nor a non-empty list of strings.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="s2">&quot;&#39;markets&#39; must be a string or list of strings, &quot;</span>
-            <span class="sa">f</span><span class="s2">&quot;got </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">value</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="si">!r}</span><span class="s2">&quot;</span>
+            <span class="s2">"'markets' must be a string or list of strings, "</span>
+            <span class="sa">f</span><span class="s2">"got </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">value</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="si">!r}</span><span class="s2">"</span>
         <span class="p">)</span>
         <span class="k">if</span> <span class="n">value</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">value</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
             <span class="k">if</span> <span class="nb">all</span><span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">item</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">value</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">value</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
                 <span class="k">return</span> <span class="n">value</span>
-            <span class="n">item_msg</span> <span class="o">=</span> <span class="s2">&quot;All items in &#39;markets&#39; must be strings.&quot;</span>
+            <span class="n">item_msg</span> <span class="o">=</span> <span class="s2">"All items in 'markets' must be strings."</span>
             <span class="k">raise</span> <span class="n">MarketsNotStringNorListStrError</span><span class="p">(</span><span class="n">item_msg</span><span class="p">)</span>
         <span class="k">raise</span> <span class="n">MarketsNotStringNorListStrError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-    <span class="nd">@model_validator</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">&quot;after&quot;</span><span class="p">)</span>
+    <span class="nd">@model_validator</span><span class="p">(</span><span class="n">mode</span><span class="o">=</span><span class="s2">"after"</span><span class="p">)</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">_dates_and_values_validate</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Pydantic validator to ensure dates and values are validated.</span>
+<span class="w">        </span><span class="sd">"""Pydantic validator to ensure dates and values are validated.</span>
 
 <span class="sd">        Raises:</span>
 <span class="sd">            ValueError: If dates are not unique or if numbers of dates and values</span>
 <span class="sd">                do not match the shape of ``tsdf``.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">values_list_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
         <span class="n">dates_list_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dates</span><span class="p">)</span>
         <span class="n">dates_set_length</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dates</span><span class="p">))</span>
         <span class="k">if</span> <span class="n">dates_list_length</span> <span class="o">!=</span> <span class="n">dates_set_length</span><span class="p">:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Dates are not unique&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Dates are not unique"</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="k">if</span> <span class="p">(</span>
             <span class="p">(</span><span class="n">dates_list_length</span> <span class="o">!=</span> <span class="n">values_list_length</span><span class="p">)</span>
             <span class="ow">or</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">)</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
             <span class="ow">or</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">)</span>
         <span class="p">):</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Number of dates and values passed do not match&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Number of dates and values passed do not match"</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="k">return</span> <span class="bp">self</span>
 
@@ -302,14 +302,14 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">dates</span><span class="p">:</span> <span class="n">DateListType</span><span class="p">,</span>
         <span class="n">values</span><span class="p">:</span> <span class="n">ValueListType</span><span class="p">,</span>
         <span class="n">valuetype</span><span class="p">:</span> <span class="n">ValueType</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
-        <span class="n">timeseries_id</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="p">,</span>
-        <span class="n">instrument_id</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="p">,</span>
+        <span class="n">timeseries_id</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">""</span><span class="p">,</span>
+        <span class="n">instrument_id</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">""</span><span class="p">,</span>
         <span class="n">isin</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">&quot;SEK&quot;</span><span class="p">,</span>
+        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">"SEK"</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">local_ccy</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create series from a list of dates and a list of values.</span>
+<span class="w">        </span><span class="sd">"""Create series from a list of dates and a list of values.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            name: String identifier of the timeseries and/or instrument.</span>
@@ -321,13 +321,13 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">            instrument_id: Database identifier of the instrument associated</span>
 <span class="sd">                with the timeseries. Optional.</span>
 <span class="sd">            isin: ISO 6166 identifier code of the associated instrument. Optional.</span>
-<span class="sd">            baseccy: ISO 4217 currency code of the timeseries. Defaults to &quot;SEK&quot;.</span>
+<span class="sd">            baseccy: ISO 4217 currency code of the timeseries. Defaults to "SEK".</span>
 <span class="sd">            local_ccy: Boolean flag indicating if timeseries is in local currency.</span>
 <span class="sd">                Defaults to True.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="bp">cls</span><span class="p">(</span>
             <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span>
             <span class="n">label</span><span class="o">=</span><span class="n">name</span><span class="p">,</span>
@@ -343,7 +343,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
                 <span class="n">data</span><span class="o">=</span><span class="n">values</span><span class="p">,</span>
                 <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">deyt</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">deyt</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">dates</span><span class="p">)],</span>
                 <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="n">name</span><span class="p">],</span> <span class="p">[</span><span class="n">valuetype</span><span class="p">]],</span>
-                <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+                <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
             <span class="p">),</span>
         <span class="p">)</span></div>
 
@@ -356,18 +356,18 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">dframe</span><span class="p">:</span> <span class="n">Series</span> <span class="o">|</span> <span class="n">DataFrame</span> <span class="o">|</span> <span class="nb">object</span><span class="p">,</span>
         <span class="n">column_nmbr</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
         <span class="n">valuetype</span><span class="p">:</span> <span class="n">ValueType</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
-        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">&quot;SEK&quot;</span><span class="p">,</span>
+        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">"SEK"</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">local_ccy</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create series from a Pandas DataFrame or Series.</span>
+<span class="w">        </span><span class="sd">"""Create series from a Pandas DataFrame or Series.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            dframe: Pandas DataFrame or Series.</span>
 <span class="sd">            column_nmbr: Using iloc[:, column_nmbr] to pick column. Defaults to 0.</span>
 <span class="sd">            valuetype: Identifies if the series is a series of values or returns.</span>
 <span class="sd">                Defaults to ValueType.PRICE.</span>
-<span class="sd">            baseccy: ISO 4217 currency code of the timeseries. Defaults to &quot;SEK&quot;.</span>
+<span class="sd">            baseccy: ISO 4217 currency code of the timeseries. Defaults to "SEK".</span>
 <span class="sd">            local_ccy: Boolean flag indicating if timeseries is in local currency.</span>
 <span class="sd">                Defaults to True.</span>
 
@@ -377,8 +377,8 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">        Raises:</span>
 <span class="sd">            TypeError: If ``dframe`` is not a ``pandas.Series`` or a</span>
 <span class="sd">                ``pandas.DataFrame``.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Argument dframe must be pandas Series or DataFrame.&quot;</span>
+<span class="sd">        """</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Argument dframe must be pandas Series or DataFrame."</span>
         <span class="n">values</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span>
         <span class="n">pandas_obj</span><span class="p">:</span> <span class="n">Series</span> <span class="o">|</span> <span class="n">DataFrame</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">dframe</span><span class="p">,</span> <span class="n">Series</span><span class="p">):</span>
@@ -395,8 +395,8 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
                 <span class="k">if</span> <span class="n">_check_if_none</span><span class="p">(</span>
                     <span class="n">dframe</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()[</span><span class="n">column_nmbr</span><span class="p">],</span>
                 <span class="p">):</span>
-                    <span class="n">label</span> <span class="o">=</span> <span class="s2">&quot;Series&quot;</span>
-                    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Label missing. Adding: </span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="s2">&quot;</span>
+                    <span class="n">label</span> <span class="o">=</span> <span class="s2">"Series"</span>
+                    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Label missing. Adding: </span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="s2">"</span>
                     <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">label</span> <span class="o">=</span> <span class="n">dframe</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()[</span><span class="n">column_nmbr</span><span class="p">]</span>
@@ -404,7 +404,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
                     <span class="n">dframe</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()[</span><span class="n">column_nmbr</span><span class="p">],</span>
                 <span class="p">):</span>
                     <span class="n">valuetype</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span>
-                    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;valuetype missing. Adding: </span><span class="si">{</span><span class="n">valuetype</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2">&quot;</span>
+                    <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"valuetype missing. Adding: </span><span class="si">{</span><span class="n">valuetype</span><span class="o">.</span><span class="n">value</span><span class="si">}</span><span class="s2">"</span>
                     <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">valuetype</span> <span class="o">=</span> <span class="n">dframe</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()[</span>
@@ -415,11 +415,11 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="k">else</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-        <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">date_fix</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">pandas_obj</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
+        <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">date_fix</span><span class="p">(</span><span class="n">d</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">pandas_obj</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
 
         <span class="k">return</span> <span class="bp">cls</span><span class="p">(</span>
-            <span class="n">timeseries_id</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
-            <span class="n">instrument_id</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
+            <span class="n">timeseries_id</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span>
+            <span class="n">instrument_id</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span>
             <span class="n">currency</span><span class="o">=</span><span class="n">baseccy</span><span class="p">,</span>
             <span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="n">label</span><span class="p">,</span>
@@ -431,7 +431,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
                 <span class="n">data</span><span class="o">=</span><span class="n">values</span><span class="p">,</span>
                 <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">deyt</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">deyt</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">dates</span><span class="p">)],</span>
                 <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="n">valuetype</span><span class="p">]],</span>
-                <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+                <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
             <span class="p">),</span>
         <span class="p">)</span></div>
 
@@ -445,13 +445,13 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">d_range</span><span class="p">:</span> <span class="n">DatetimeIndex</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">days</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">end_dt</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">label</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;Series&quot;</span><span class="p">,</span>
+        <span class="n">label</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"Series"</span><span class="p">,</span>
         <span class="n">valuetype</span><span class="p">:</span> <span class="n">ValueType</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
-        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">&quot;SEK&quot;</span><span class="p">,</span>
+        <span class="n">baseccy</span><span class="p">:</span> <span class="n">CurrencyStringType</span> <span class="o">=</span> <span class="s2">"SEK"</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">local_ccy</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create series from values accruing with a given fixed rate return.</span>
+<span class="w">        </span><span class="sd">"""Create series from values accruing with a given fixed rate return.</span>
 
 <span class="sd">        Providing a date_range of type Pandas DatetimeIndex takes priority over</span>
 <span class="sd">        providing a combination of days and an end date.</span>
@@ -466,7 +466,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">            label: Placeholder for a name of the timeseries.</span>
 <span class="sd">            valuetype: Identifies if the series is a series of values or returns.</span>
 <span class="sd">                Defaults to ValueType.PRICE.</span>
-<span class="sd">            baseccy: The currency of the timeseries. Defaults to &quot;SEK&quot;.</span>
+<span class="sd">            baseccy: The currency of the timeseries. Defaults to "SEK".</span>
 <span class="sd">            local_ccy: Boolean flag indicating if timeseries is in local currency.</span>
 <span class="sd">                Defaults to True.</span>
 
@@ -476,22 +476,22 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">        Raises:</span>
 <span class="sd">            IncorrectArgumentComboError: If ``d_range`` is not provided and the</span>
 <span class="sd">                combination of ``days`` and ``end_dt`` is incomplete.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="n">d_range</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="k">if</span> <span class="n">days</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">end_dt</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
                 <span class="n">d_range</span> <span class="o">=</span> <span class="n">DatetimeIndex</span><span class="p">(</span>
-                    <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">date_range</span><span class="p">(</span><span class="n">periods</span><span class="o">=</span><span class="n">days</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">end_dt</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;D&quot;</span><span class="p">)],</span>
+                    <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">date_range</span><span class="p">(</span><span class="n">periods</span><span class="o">=</span><span class="n">days</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">end_dt</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">"D"</span><span class="p">)],</span>
                 <span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;If d_range is not provided both days and end_dt must be.&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="s2">"If d_range is not provided both days and end_dt must be."</span>
                 <span class="k">raise</span> <span class="n">IncorrectArgumentComboError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
         <span class="n">deltas</span> <span class="o">=</span> <span class="n">array</span><span class="p">([</span><span class="n">i</span><span class="o">.</span><span class="n">days</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">d_range</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="n">d_range</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]])</span>
         <span class="n">arr</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">cumprod</span><span class="p">(</span><span class="n">insert</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">deltas</span> <span class="o">*</span> <span class="n">rate</span> <span class="o">/</span> <span class="mi">365</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)))</span>
-        <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">d_range</span><span class="p">]</span>
+        <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">d_range</span><span class="p">]</span>
 
         <span class="k">return</span> <span class="bp">cls</span><span class="p">(</span>
-            <span class="n">timeseries_id</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
-            <span class="n">instrument_id</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
+            <span class="n">timeseries_id</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span>
+            <span class="n">instrument_id</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span>
             <span class="n">currency</span><span class="o">=</span><span class="n">baseccy</span><span class="p">,</span>
             <span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="n">label</span><span class="p">,</span>
@@ -503,7 +503,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
                 <span class="n">data</span><span class="o">=</span><span class="n">arr</span><span class="p">,</span>
                 <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">dates</span><span class="p">)],</span>
                 <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="n">valuetype</span><span class="p">]],</span>
-                <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+                <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
             <span class="p">),</span>
         <span class="p">)</span></div>
 
@@ -511,27 +511,27 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenTimeSeries.from_deepcopy">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.from_deepcopy">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">from_deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create copy of OpenTimeSeries object.</span>
+<span class="w">        </span><span class="sd">"""Create copy of OpenTimeSeries object.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></div>
 
 
 <div class="viewcode-block" id="OpenTimeSeries.pandas_df">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.pandas_df">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">pandas_df</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Populate .tsdf Pandas DataFrame from the .dates and .values lists.</span>
+<span class="w">        </span><span class="sd">"""Populate .tsdf Pandas DataFrame from the .dates and .values lists.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">dframe</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dates</span><span class="p">)],</span>
             <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]],</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">dframe</span>
 
@@ -544,7 +544,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
         <span class="n">properties</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">LiteralSeriesProps</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate chosen properties.</span>
+<span class="w">        </span><span class="sd">"""Calculate chosen properties.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            properties: The properties to calculate. Defaults to calculating all</span>
@@ -552,10 +552,10 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Properties of the OpenTimeSeries.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">properties</span><span class="p">:</span>
             <span class="n">properties</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;list[LiteralSeriesProps]&quot;</span><span class="p">,</span>
+                <span class="s2">"list[LiteralSeriesProps]"</span><span class="p">,</span>
                 <span class="n">OpenTimeSeriesPropertiesList</span><span class="o">.</span><span class="n">allowed_strings</span><span class="p">,</span>
             <span class="p">)</span>
 
@@ -564,13 +564,13 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="k">def</span><span class="w"> </span><span class="nf">_prop_value</span><span class="p">(</span><span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span> <span class="o">|</span> <span class="nb">int</span> <span class="o">|</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
             <span class="n">attr</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
             <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-                <span class="s2">&quot;float | int | dt.date | Series[float]&quot;</span><span class="p">,</span>
+                <span class="s2">"float | int | dt.date | Series[float]"</span><span class="p">,</span>
                 <span class="n">attr</span><span class="p">()</span> <span class="k">if</span> <span class="nb">callable</span><span class="p">(</span><span class="n">attr</span><span class="p">)</span> <span class="k">else</span> <span class="n">attr</span><span class="p">,</span>
             <span class="p">)</span>
 
         <span class="n">pdf</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="o">.</span><span class="n">from_dict</span><span class="p">(</span>
             <span class="p">{</span><span class="n">x</span><span class="p">:</span> <span class="n">_prop_value</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">props</span><span class="p">},</span>
-            <span class="n">orient</span><span class="o">=</span><span class="s2">&quot;index&quot;</span><span class="p">,</span>
+            <span class="n">orient</span><span class="o">=</span><span class="s2">"index"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">pdf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span>
         <span class="k">return</span> <span class="n">pdf</span></div>
@@ -579,15 +579,15 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenTimeSeries.value_to_ret">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.value_to_ret">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">value_to_ret</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of values into series of returns.</span>
+<span class="w">        </span><span class="sd">"""Convert series of values into series of returns.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            The returns of the values in the series.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
         <span class="n">returns</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
-        <span class="n">arrays</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Any&quot;</span><span class="p">,</span> <span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]])</span>
+        <span class="n">arrays</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Any"</span><span class="p">,</span> <span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]])</span>
         <span class="n">returns</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">arrays</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">returns</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
         <span class="k">return</span> <span class="bp">self</span></div>
@@ -596,7 +596,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenTimeSeries.value_to_diff">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.value_to_diff">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">value_to_diff</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">periods</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of values to series of their period differences.</span>
+<span class="w">        </span><span class="sd">"""Convert series of values to series of their period differences.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            periods: The number of periods between observations over which difference</span>
@@ -604,7 +604,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">periods</span><span class="o">=</span><span class="n">periods</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
@@ -620,11 +620,11 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="OpenTimeSeries.to_cumret">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.to_cumret">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">to_cumret</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of returns into cumulative series of values.</span>
+<span class="w">        </span><span class="sd">"""Convert series of returns into cumulative series of values.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
 
@@ -648,7 +648,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">days_in_year</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">365</span><span class="p">,</span>
         <span class="n">divider</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Convert series of 1-day rates into series of cumulative values.</span>
+<span class="w">        </span><span class="sd">"""Convert series of 1-day rates into series of cumulative values.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            days_in_year: Calendar days per year used as divisor. Defaults to 365.</span>
@@ -657,12 +657,12 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">arr</span><span class="p">:</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">float64</span><span class="p">]</span> <span class="o">=</span> <span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">)</span> <span class="o">/</span> <span class="n">divider</span>
 
         <span class="n">deltas</span> <span class="o">=</span> <span class="n">array</span><span class="p">([</span><span class="n">i</span><span class="o">.</span><span class="n">days</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]])</span>
         <span class="n">arr</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span>
+            <span class="s2">"NDArray[float64]"</span><span class="p">,</span>
             <span class="n">cumprod</span><span class="p">(</span>
                 <span class="n">a</span><span class="o">=</span><span class="n">insert</span><span class="p">(</span>
                     <span class="n">arr</span><span class="o">=</span><span class="mf">1.0</span> <span class="o">+</span> <span class="n">deltas</span> <span class="o">*</span> <span class="n">arr</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">/</span> <span class="n">days_in_year</span><span class="p">,</span> <span class="n">obj</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="mf">1.0</span>
@@ -670,14 +670,14 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
             <span class="p">),</span>
         <span class="p">)</span>
 
-        <span class="bp">self</span><span class="o">.</span><span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">values</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">values</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dates</span><span class="p">)],</span>
             <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]],</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span>
 
         <span class="k">return</span> <span class="bp">self</span></div>
@@ -687,17 +687,17 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.resample">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">resample</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
-        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;BME&quot;</span><span class="p">,</span>
+        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"BME"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Resamples the timeseries frequency.</span>
+<span class="w">        </span><span class="sd">"""Resamples the timeseries frequency.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            freq: The date offset string that sets the resampled frequency.</span>
-<span class="sd">                Defaults to &quot;BME&quot;.</span>
+<span class="sd">                Defaults to "BME".</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
@@ -711,10 +711,10 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.resample_to_business_period_ends">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">resample_to_business_period_ends</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span>
-        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">&quot;BME&quot;</span><span class="p">,</span>
-        <span class="n">method</span><span class="p">:</span> <span class="n">LiteralPandasReindexMethod</span> <span class="o">=</span> <span class="s2">&quot;nearest&quot;</span><span class="p">,</span>
+        <span class="n">freq</span><span class="p">:</span> <span class="n">LiteralBizDayFreq</span> <span class="o">=</span> <span class="s2">"BME"</span><span class="p">,</span>
+        <span class="n">method</span><span class="p">:</span> <span class="n">LiteralPandasReindexMethod</span> <span class="o">=</span> <span class="s2">"nearest"</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Resamples timeseries frequency to the business calendar month end dates.</span>
+<span class="w">        </span><span class="sd">"""Resamples timeseries frequency to the business calendar month end dates.</span>
 
 <span class="sd">        Stubs left in place. Stubs will be aligned to the shortest stub.</span>
 
@@ -731,12 +731,12 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">            ResampleDataLossError: If called on a return series (``valuetype`` is</span>
 <span class="sd">                ``ValueType.RTRN``), since summation across sparser frequency would</span>
 <span class="sd">                be required to avoid data loss.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">:</span>
             <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
-                <span class="s2">&quot;Do not run resample_to_business_period_ends on return series. &quot;</span>
-                <span class="s2">&quot;The operation will pick the last data point in the sparser series. &quot;</span>
-                <span class="s2">&quot;It will not sum returns and therefore data will be lost.&quot;</span>
+                <span class="s2">"Do not run resample_to_business_period_ends on return series. "</span>
+                <span class="s2">"The operation will pick the last data point in the sparser series. "</span>
+                <span class="s2">"It will not sum returns and therefore data will be lost."</span>
             <span class="p">)</span>
             <span class="k">raise</span> <span class="n">ResampleDataLossError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
@@ -762,7 +762,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Exponentially Weighted Moving Average Model for Volatility.</span>
+<span class="w">        </span><span class="sd">"""Exponentially Weighted Moving Average Model for Volatility.</span>
 
 <span class="sd">        Reference: https://www.investopedia.com/articles/07/ewma.asp.</span>
 
@@ -781,7 +781,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Series EWMA volatility.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
             <span class="n">from_dt</span><span class="o">=</span><span class="n">from_date</span><span class="p">,</span>
@@ -789,7 +789,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="p">)</span>
         <span class="n">time_factor</span> <span class="o">=</span> <span class="n">_calculate_time_factor</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-                <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+                <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
             <span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span>
             <span class="n">earlier</span><span class="o">=</span><span class="n">earlier</span><span class="p">,</span>
             <span class="n">later</span><span class="o">=</span><span class="n">later</span><span class="p">,</span>
@@ -797,7 +797,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="p">)</span>
 
         <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
         <span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
 
         <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">)]</span> <span class="o">=</span> <span class="n">log</span><span class="p">(</span>
@@ -823,7 +823,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="n">rawdata</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">EWMA_VOL</span><span class="p">),</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -840,7 +840,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">to_date</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">periods_in_a_year_fixed</span><span class="p">:</span> <span class="n">DaysInYearType</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Exponentially Weighted Moving Average Model for Value At Risk (VaR).</span>
+<span class="w">        </span><span class="sd">"""Exponentially Weighted Moving Average Model for Value At Risk (VaR).</span>
 
 <span class="sd">        Reference: https://www.investopedia.com/articles/07/ewma.asp.</span>
 
@@ -860,7 +860,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Series EWMA VaR.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">earlier</span><span class="p">,</span> <span class="n">later</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calc_range</span><span class="p">(</span>
             <span class="n">months_offset</span><span class="o">=</span><span class="n">months_from_last</span><span class="p">,</span>
             <span class="n">from_dt</span><span class="o">=</span><span class="n">from_date</span><span class="p">,</span>
@@ -868,7 +868,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="p">)</span>
         <span class="n">time_factor</span> <span class="o">=</span> <span class="n">_calculate_time_factor</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-                <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+                <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
             <span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span>
             <span class="n">earlier</span><span class="o">=</span><span class="n">earlier</span><span class="p">,</span>
             <span class="n">later</span><span class="o">=</span><span class="n">later</span><span class="p">,</span>
@@ -876,7 +876,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="p">)</span>
 
         <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span>
-            <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;Timestamp&quot;</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
+            <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">earlier</span><span class="p">)</span> <span class="p">:</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"Timestamp"</span><span class="p">,</span> <span class="n">later</span><span class="p">)</span>
         <span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
 
         <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">)]</span> <span class="o">=</span> <span class="n">log</span><span class="p">(</span>
@@ -902,7 +902,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="n">array</span><span class="p">(</span><span class="n">rawdata</span><span class="p">)</span> <span class="o">*</span> <span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">level</span><span class="p">),</span>
             <span class="n">index</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
             <span class="n">name</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">EWMA_VAR</span><span class="p">),</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -913,7 +913,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="n">adjustment</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
         <span class="n">days_in_year</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">365</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Add or subtract a fee from the timeseries return.</span>
+<span class="w">        </span><span class="sd">"""Add or subtract a fee from the timeseries return.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            adjustment: Fee to add or subtract.</span>
@@ -922,13 +922,13 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">==</span> <span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">:</span>
             <span class="n">ra_df</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
             <span class="n">initial_value</span> <span class="o">=</span> <span class="mf">1.0</span>
             <span class="n">returns_input</span> <span class="o">=</span> <span class="kc">True</span>
         <span class="k">else</span><span class="p">:</span>
-            <span class="n">initial_value</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
+            <span class="n">initial_value</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
             <span class="n">ra_df</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span>
             <span class="n">returns_input</span> <span class="o">=</span> <span class="kc">False</span>
         <span class="n">ra_df</span> <span class="o">=</span> <span class="n">ra_df</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span>
@@ -938,15 +938,15 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
         <span class="n">dates_np</span> <span class="o">=</span> <span class="n">array</span><span class="p">(</span>
             <span class="p">[</span><span class="n">dt</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">combine</span><span class="p">(</span><span class="n">d</span><span class="p">,</span> <span class="n">dt</span><span class="o">.</span><span class="n">time</span><span class="p">())</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">dates_list</span><span class="p">],</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;datetime64[D]&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"datetime64[D]"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">date_diffs</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span>
-            <span class="n">diff</span><span class="p">(</span><span class="n">dates_np</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s2">&quot;timedelta64[D]&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">float64</span><span class="p">),</span>
+            <span class="s2">"NDArray[float64]"</span><span class="p">,</span>
+            <span class="n">diff</span><span class="p">(</span><span class="n">dates_np</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s2">"timedelta64[D]"</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">float64</span><span class="p">),</span>
         <span class="p">)</span>
 
         <span class="n">returns_array</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;NDArray[float64]&quot;</span><span class="p">,</span>
+            <span class="s2">"NDArray[float64]"</span><span class="p">,</span>
             <span class="n">ra_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">(),</span>
         <span class="p">)</span>
 
@@ -980,7 +980,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">delete_lvl_one</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Set the column labels of the .tsdf Pandas Dataframe.</span>
+<span class="w">        </span><span class="sd">"""Set the column labels of the .tsdf Pandas Dataframe.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lvl_zero: New level zero label. Optional.</span>
@@ -989,7 +989,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            An OpenTimeSeries object.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="n">lvl_zero</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">lvl_one</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
                 <span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]],</span>
@@ -1002,14 +1002,14 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
             <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">lvl_one</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">([[</span><span class="n">lvl_zero</span><span class="p">],</span> <span class="p">[</span><span class="n">lvl_one</span><span class="p">]])</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">lvl_zero</span><span class="p">,</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;ValueType&quot;</span><span class="p">,</span> <span class="n">lvl_one</span><span class="p">)</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">label</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span> <span class="o">=</span> <span class="n">lvl_zero</span><span class="p">,</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"ValueType"</span><span class="p">,</span> <span class="n">lvl_one</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">delete_lvl_one</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
         <span class="k">return</span> <span class="bp">self</span></div>
 
 
     <span class="k">def</span><span class="w"> </span><span class="nf">_returns_series</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">squared</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return demeaned return series for autocorrelation analysis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">"""Return demeaned return series for autocorrelation analysis."""</span>
         <span class="n">data</span><span class="p">:</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
         <span class="k">return</span> <span class="n">_demeaned_returns_for_autocorr</span><span class="p">(</span>
             <span class="n">series</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">valuetype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">valuetype</span><span class="p">,</span> <span class="n">squared</span><span class="o">=</span><span class="n">squared</span>
@@ -1023,7 +1023,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">squared</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate autocorrelation function for specified lags.</span>
+<span class="w">        </span><span class="sd">"""Calculate autocorrelation function for specified lags.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lags: If int, compute ACF from lag 0 to this value (inclusive).</span>
@@ -1032,7 +1032,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Series of autocorrelations indexed by lag.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">rets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returns_series</span><span class="p">(</span><span class="n">squared</span><span class="o">=</span><span class="n">squared</span><span class="p">)</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">lags</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
             <span class="n">lag_list</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">lags</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
@@ -1047,15 +1047,15 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="n">values</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="n">lag_list</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;ACF&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"ACF"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
 <div class="viewcode-block" id="OpenTimeSeries.partial_autocorr">
 <a class="viewcode-back" href="../../api/series.html#openseries.OpenTimeSeries.partial_autocorr">[docs]</a>
     <span class="k">def</span><span class="w"> </span><span class="nf">partial_autocorr</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">lag</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">squared</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate partial autocorrelation at a given lag.</span>
+<span class="w">        </span><span class="sd">"""Calculate partial autocorrelation at a given lag.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lag: The lag at which to compute partial autocorrelation. Defaults to 1.</span>
@@ -1064,7 +1064,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Partial autocorrelation at the specified lag.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">pacf_series</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pacf</span><span class="p">(</span><span class="n">lags</span><span class="o">=</span><span class="n">lag</span><span class="p">,</span> <span class="n">squared</span><span class="o">=</span><span class="n">squared</span><span class="p">)</span>
         <span class="k">return</span> <span class="nb">float</span><span class="p">(</span><span class="n">pacf_series</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">lag</span><span class="p">])</span></div>
 
@@ -1077,7 +1077,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">squared</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Series</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculate partial autocorrelation function for specified lags.</span>
+<span class="w">        </span><span class="sd">"""Calculate partial autocorrelation function for specified lags.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lags: If int, compute PACF from lag 0 to this value (inclusive).</span>
@@ -1086,7 +1086,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Series of partial autocorrelations indexed by lag.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">lags</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
             <span class="n">lag_list</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">lags</span> <span class="o">+</span> <span class="mi">1</span><span class="p">))</span>
         <span class="k">else</span><span class="p">:</span>
@@ -1116,8 +1116,8 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">Series</span><span class="p">(</span>
             <span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="n">result</span><span class="p">[</span><span class="n">lag</span><span class="p">]</span> <span class="k">for</span> <span class="n">lag</span> <span class="ow">in</span> <span class="n">lag_list</span><span class="p">],</span>
             <span class="n">index</span><span class="o">=</span><span class="n">lag_list</span><span class="p">,</span>
-            <span class="n">name</span><span class="o">=</span><span class="s2">&quot;PACF&quot;</span><span class="p">,</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">name</span><span class="o">=</span><span class="s2">"PACF"</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span></div>
 
 
@@ -1129,7 +1129,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">squared</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]]:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Compute Ljung-Box test for autocorrelation.</span>
+<span class="w">        </span><span class="sd">"""Compute Ljung-Box test for autocorrelation.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            lags: If int, use lags 1 through this value. If list, use the given</span>
@@ -1141,7 +1141,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 <span class="sd">            Tuple of (statistic, pvalue, lags) where statistic is the Ljung-Box</span>
 <span class="sd">            Q statistic, pvalue is the chi-squared p-value, and lags is the</span>
 <span class="sd">            list of lags used.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">rets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_returns_series</span><span class="p">(</span><span class="n">squared</span><span class="o">=</span><span class="n">squared</span><span class="p">)</span>
         <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">rets</span><span class="p">)</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">lags</span><span class="p">,</span> <span class="nb">int</span><span class="p">):</span>
@@ -1170,7 +1170,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
     <span class="n">back</span><span class="p">:</span> <span class="n">TypeOpenTimeSeries</span><span class="p">,</span>
     <span class="n">old_fee</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">TypeOpenTimeSeries</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Chain two timeseries together.</span>
+<span class="w">    </span><span class="sd">"""Chain two timeseries together.</span>
 
 <span class="sd">    The function assumes that the two series have at least one date in common.</span>
 
@@ -1181,7 +1181,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        An OpenTimeSeries object or a subclass thereof.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">old</span> <span class="o">=</span> <span class="n">front</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
     <span class="n">old</span><span class="o">.</span><span class="n">running_adjustment</span><span class="p">(</span><span class="n">old_fee</span><span class="p">)</span>
     <span class="n">new</span> <span class="o">=</span> <span class="n">back</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">()</span>
@@ -1189,17 +1189,17 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
     <span class="n">first</span> <span class="o">=</span> <span class="n">new</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
 
     <span class="k">if</span> <span class="n">old</span><span class="o">.</span><span class="n">last_idx</span> <span class="o">&lt;</span> <span class="n">first</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Timeseries dates must overlap to allow them to be chained.&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Timeseries dates must overlap to allow them to be chained."</span>
         <span class="k">raise</span> <span class="n">DateAlignmentError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
     <span class="k">while</span> <span class="n">first</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">old</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
         <span class="n">idx</span> <span class="o">+=</span> <span class="mi">1</span>
         <span class="n">first</span> <span class="o">=</span> <span class="n">new</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
         <span class="k">if</span> <span class="n">first</span> <span class="o">&gt;</span> <span class="n">old</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]:</span>
-            <span class="n">msg</span> <span class="o">=</span> <span class="s2">&quot;Failed to find a matching date between series&quot;</span>
+            <span class="n">msg</span> <span class="o">=</span> <span class="s2">"Failed to find a matching date between series"</span>
             <span class="k">raise</span> <span class="n">DateAlignmentError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
-    <span class="n">dates</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">old</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span> <span class="k">if</span> <span class="n">x</span> <span class="o">&lt;</span> <span class="n">first</span><span class="p">]</span>
+    <span class="n">dates</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">old</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span> <span class="k">if</span> <span class="n">x</span> <span class="o">&lt;</span> <span class="n">first</span><span class="p">]</span>
 
     <span class="n">old_values</span> <span class="o">=</span> <span class="n">Series</span><span class="p">(</span><span class="n">old</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:</span> <span class="nb">len</span><span class="p">(</span><span class="n">dates</span><span class="p">),</span> <span class="mi">0</span><span class="p">])</span>
     <span class="n">old_values</span> <span class="o">=</span> <span class="n">old_values</span><span class="o">.</span><span class="n">mul</span><span class="p">(</span>
@@ -1208,7 +1208,7 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
     <span class="p">)</span>
     <span class="n">values</span> <span class="o">=</span> <span class="n">append</span><span class="p">(</span><span class="n">old_values</span><span class="p">,</span> <span class="n">new</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">])</span>
 
-    <span class="n">dates</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y-%m-</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">new</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
+    <span class="n">dates</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">"%Y-%m-</span><span class="si">%d</span><span class="s2">"</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">new</span><span class="o">.</span><span class="n">tsdf</span><span class="o">.</span><span class="n">index</span><span class="p">])</span>
 
     <span class="k">return</span> <span class="n">back</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span>
         <span class="n">timeseries_id</span><span class="o">=</span><span class="n">new</span><span class="o">.</span><span class="n">timeseries_id</span><span class="p">,</span>
@@ -1224,26 +1224,26 @@ <h1>Source code for openseries.series</h1><div class="highlight"><pre>
             <span class="n">data</span><span class="o">=</span><span class="n">values</span><span class="p">,</span>
             <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">date</span><span class="p">()</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">dates</span><span class="p">)],</span>
             <span class="n">columns</span><span class="o">=</span><span class="p">[[</span><span class="n">new</span><span class="o">.</span><span class="n">label</span><span class="p">],</span> <span class="p">[</span><span class="n">new</span><span class="o">.</span><span class="n">valuetype</span><span class="p">]],</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">),</span>
     <span class="p">)</span></div>
 
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_check_if_none</span><span class="p">(</span><span class="n">item</span><span class="p">:</span> <span class="nb">object</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Check if a variable is None or equivalent.</span>
+<span class="w">    </span><span class="sd">"""Check if a variable is None or equivalent.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        item: Variable to be checked.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Answer to whether the variable is None or equivalent.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">item</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="k">return</span> <span class="kc">True</span>
 
     <span class="k">try</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">&quot;bool&quot;</span><span class="p">,</span> <span class="n">isnan</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;float&quot;</span><span class="p">,</span> <span class="n">item</span><span class="p">)))</span>
+        <span class="k">return</span> <span class="n">cast</span><span class="p">(</span><span class="s2">"bool"</span><span class="p">,</span> <span class="n">isnan</span><span class="p">(</span><span class="n">cast</span><span class="p">(</span><span class="s2">"float"</span><span class="p">,</span> <span class="n">item</span><span class="p">)))</span>
     <span class="k">except</span> <span class="p">(</span><span class="ne">TypeError</span><span class="p">,</span> <span class="ne">ValueError</span><span class="p">):</span>
         <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">item</span><span class="p">))</span> <span class="o">==</span> <span class="mi">0</span>
 </pre></div>
diff --git a/docs/build/html/_modules/openseries/simulation.html b/docs/build/html/_modules/openseries/simulation.html
index c5dfa0a2..6fb00d83 100644
--- a/docs/build/html/_modules/openseries/simulation.html
+++ b/docs/build/html/_modules/openseries/simulation.html
@@ -108,7 +108,7 @@
            <div itemprop="articleBody">
              
   <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
-<span></span><span class="sd">&quot;&quot;&quot;The ReturnSimulation class.&quot;&quot;&quot;</span>
+<span></span><span class="sd">"""The ReturnSimulation class."""</span>
 
 <span class="kn">from</span><span class="w"> </span><span class="nn">__future__</span><span class="w"> </span><span class="kn">import</span> <span class="n">annotations</span>
 
@@ -146,11 +146,11 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
     <span class="n">ValueType</span><span class="p">,</span>
 <span class="p">)</span>
 
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;ReturnSimulation&quot;</span><span class="p">]</span>
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"ReturnSimulation"</span><span class="p">]</span>
 
 
 <span class="k">class</span><span class="w"> </span><span class="nc">_JumpParams</span><span class="p">(</span><span class="n">TypedDict</span><span class="p">,</span> <span class="n">total</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;TypedDict for jump diffusion parameters.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""TypedDict for jump diffusion parameters."""</span>
 
     <span class="n">jumps_lamda</span><span class="p">:</span> <span class="n">NonNegativeFloat</span>
     <span class="n">jumps_sigma</span><span class="p">:</span> <span class="n">NonNegativeFloat</span>
@@ -158,14 +158,14 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_validate_ar1_coef</span><span class="p">(</span><span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Validate ar1_coef is in (-1, 1) for stationarity.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">"""Validate ar1_coef is in (-1, 1) for stationarity."""</span>
     <span class="k">if</span> <span class="ow">not</span> <span class="o">-</span><span class="mf">1.0</span> <span class="o">&lt;</span> <span class="n">ar1_coef</span> <span class="o">&lt;</span> <span class="mf">1.0</span><span class="p">:</span>
-        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;ar1_coef must be in (-1, 1) for stationarity, got </span><span class="si">{</span><span class="n">ar1_coef</span><span class="si">}</span><span class="s2">&quot;</span>
+        <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"ar1_coef must be in (-1, 1) for stationarity, got </span><span class="si">{</span><span class="n">ar1_coef</span><span class="si">}</span><span class="s2">"</span>
         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_apply_ar1_filter</span><span class="p">(</span><span class="n">returns</span><span class="p">:</span> <span class="n">DataFrame</span><span class="p">,</span> <span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Apply AR(1) filter to returns to introduce lag-1 autocorrelation.</span>
+<span class="w">    </span><span class="sd">"""Apply AR(1) filter to returns to introduce lag-1 autocorrelation.</span>
 
 <span class="sd">    r_t = ar1_coef * r_{t-1} + sqrt(1 - ar1_coef**2) * innovation_t</span>
 <span class="sd">    Preserves mean and variance of the base process.</span>
@@ -176,27 +176,27 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Filtered returns.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">if</span> <span class="n">ar1_coef</span> <span class="o">==</span> <span class="mf">0.0</span><span class="p">:</span>
         <span class="k">return</span> <span class="n">returns</span>
     <span class="n">arr</span> <span class="o">=</span> <span class="n">returns</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">(</span><span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="n">scale</span> <span class="o">=</span> <span class="n">sqrt</span><span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="n">ar1_coef</span> <span class="o">*</span> <span class="n">ar1_coef</span><span class="p">)</span>
     <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">arr</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
         <span class="n">arr</span><span class="p">[:,</span> <span class="n">t</span><span class="p">]</span> <span class="o">=</span> <span class="n">ar1_coef</span> <span class="o">*</span> <span class="n">arr</span><span class="p">[:,</span> <span class="n">t</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">scale</span> <span class="o">*</span> <span class="n">arr</span><span class="p">[:,</span> <span class="n">t</span><span class="p">]</span>
-    <span class="k">return</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">arr</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">arr</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">)</span>
 
 
 <span class="k">def</span><span class="w"> </span><span class="nf">_random_generator</span><span class="p">(</span><span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Generator</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Make a Numpy Random Generator object.</span>
+<span class="w">    </span><span class="sd">"""Make a Numpy Random Generator object.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        seed: Random seed.</span>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        Numpy random process generator.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="n">ss</span> <span class="o">=</span> <span class="n">SeedSequence</span><span class="p">(</span><span class="n">entropy</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
-    <span class="n">bg</span> <span class="o">=</span> <span class="n">PCG64</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">cast</span><span class="p">(</span><span class="s2">&quot;int | None&quot;</span><span class="p">,</span> <span class="n">ss</span><span class="p">))</span>
+    <span class="n">bg</span> <span class="o">=</span> <span class="n">PCG64</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">cast</span><span class="p">(</span><span class="s2">"int | None"</span><span class="p">,</span> <span class="n">ss</span><span class="p">))</span>
     <span class="k">return</span> <span class="n">Generator</span><span class="p">(</span><span class="n">bit_generator</span><span class="o">=</span><span class="n">bg</span><span class="p">)</span>
 
 
@@ -211,7 +211,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
     <span class="n">seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Unpack</span><span class="p">[</span><span class="n">_JumpParams</span><span class="p">],</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ReturnSimulation</span><span class="p">:</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;Common logic for creating simulations.</span>
+<span class="w">    </span><span class="sd">"""Common logic for creating simulations.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        cls: The ReturnSimulation class.</span>
@@ -226,7 +226,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">    Returns:</span>
 <span class="sd">        A ReturnSimulation instance.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
     <span class="k">return</span> <span class="bp">cls</span><span class="p">(</span>
         <span class="n">number_of_sims</span><span class="o">=</span><span class="n">number_of_sims</span><span class="p">,</span>
         <span class="n">trading_days</span><span class="o">=</span><span class="n">trading_days</span><span class="p">,</span>
@@ -242,7 +242,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ReturnSimulation">
 <a class="viewcode-back" href="../../api/simulation.html#openseries.ReturnSimulation">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">ReturnSimulation</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span>
-<span class="w">    </span><span class="sd">&quot;&quot;&quot;The class ReturnSimulation allows for simulating financial timeseries.</span>
+<span class="w">    </span><span class="sd">"""The class ReturnSimulation allows for simulating financial timeseries.</span>
 
 <span class="sd">    Args:</span>
 <span class="sd">        number_of_sims: Number of simulations to generate.</span>
@@ -257,7 +257,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 <span class="sd">        jumps_mu: This is the average jump size. Defaults to 0.0.</span>
 <span class="sd">        seed: Seed for random process initiation.</span>
 
-<span class="sd">    &quot;&quot;&quot;</span>
+<span class="sd">    """</span>
 
     <span class="n">number_of_sims</span><span class="p">:</span> <span class="n">PositiveInt</span>
     <span class="n">trading_days</span><span class="p">:</span> <span class="n">PositiveInt</span>
@@ -273,30 +273,30 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
     <span class="n">model_config</span> <span class="o">=</span> <span class="n">ConfigDict</span><span class="p">(</span>
         <span class="n">arbitrary_types_allowed</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
         <span class="n">validate_assignment</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-        <span class="n">revalidate_instances</span><span class="o">=</span><span class="s2">&quot;always&quot;</span><span class="p">,</span>
+        <span class="n">revalidate_instances</span><span class="o">=</span><span class="s2">"always"</span><span class="p">,</span>
     <span class="p">)</span>
 
 <div class="viewcode-block" id="ReturnSimulation.results">
 <a class="viewcode-back" href="../../api/simulation.html#openseries.ReturnSimulation.results">[docs]</a>
     <span class="nd">@cached_property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">results</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Simulation data.</span>
+<span class="w">        </span><span class="sd">"""Simulation data.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Simulation data.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">dframe</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span><span class="o">.</span><span class="n">cumprod</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">T</span></div>
+<span class="sd">        """</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">dframe</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span><span class="o">.</span><span class="n">cumprod</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">)</span><span class="o">.</span><span class="n">T</span></div>
 
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">realized_mean_return</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Annualized arithmetic mean of returns.</span>
+<span class="w">        </span><span class="sd">"""Annualized arithmetic mean of returns.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Annualized arithmetic mean of returns.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;float&quot;</span><span class="p">,</span>
+            <span class="s2">"float"</span><span class="p">,</span>
             <span class="p">(</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">results</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">trading_days_in_year</span>
             <span class="p">)</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span>
@@ -304,13 +304,13 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
     <span class="nd">@property</span>
     <span class="k">def</span><span class="w"> </span><span class="nf">realized_vol</span><span class="p">(</span><span class="bp">self</span><span class="p">:</span> <span class="n">Self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Annualized volatility.</span>
+<span class="w">        </span><span class="sd">"""Annualized volatility.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Annualized volatility.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="k">return</span> <span class="n">cast</span><span class="p">(</span>
-            <span class="s2">&quot;float&quot;</span><span class="p">,</span>
+            <span class="s2">"float"</span><span class="p">,</span>
             <span class="p">(</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">results</span><span class="o">.</span><span class="n">ffill</span><span class="p">()</span><span class="o">.</span><span class="n">pct_change</span><span class="p">()</span><span class="o">.</span><span class="n">std</span><span class="p">()</span>
                 <span class="o">*</span> <span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">trading_days_in_year</span><span class="p">)</span>
@@ -331,7 +331,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">randomizer</span><span class="p">:</span> <span class="n">Generator</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ReturnSimulation</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a Normal distribution simulation.</span>
+<span class="w">        </span><span class="sd">"""Create a Normal distribution simulation.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            number_of_sims: Number of simulations to generate.</span>
@@ -347,7 +347,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Normal distribution simulation.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">_validate_ar1_coef</span><span class="p">(</span><span class="n">ar1_coef</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">randomizer</span><span class="p">:</span>
             <span class="n">randomizer</span> <span class="o">=</span> <span class="n">_random_generator</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
@@ -358,7 +358,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
                 <span class="n">scale</span><span class="o">=</span><span class="n">mean_annual_vol</span> <span class="o">/</span> <span class="n">sqrt</span><span class="p">(</span><span class="n">trading_days_in_year</span><span class="p">),</span>
                 <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">number_of_sims</span><span class="p">,</span> <span class="n">trading_days</span><span class="p">),</span>
             <span class="p">),</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="n">_apply_ar1_filter</span><span class="p">(</span><span class="n">returns_df</span><span class="p">,</span> <span class="n">ar1_coef</span><span class="p">)</span>
 
@@ -388,7 +388,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">randomizer</span><span class="p">:</span> <span class="n">Generator</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ReturnSimulation</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a Lognormal distribution simulation.</span>
+<span class="w">        </span><span class="sd">"""Create a Lognormal distribution simulation.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            number_of_sims: Number of simulations to generate.</span>
@@ -404,7 +404,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Lognormal distribution simulation.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">_validate_ar1_coef</span><span class="p">(</span><span class="n">ar1_coef</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">randomizer</span><span class="p">:</span>
             <span class="n">randomizer</span> <span class="o">=</span> <span class="n">_random_generator</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
@@ -418,7 +418,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
                 <span class="p">)</span>
                 <span class="o">-</span> <span class="mi">1</span>
             <span class="p">),</span>
-            <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">,</span>
+            <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">,</span>
         <span class="p">)</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="n">_apply_ar1_filter</span><span class="p">(</span><span class="n">returns_df</span><span class="p">,</span> <span class="n">ar1_coef</span><span class="p">)</span>
 
@@ -448,7 +448,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">randomizer</span><span class="p">:</span> <span class="n">Generator</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ReturnSimulation</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a Geometric Brownian Motion simulation.</span>
+<span class="w">        </span><span class="sd">"""Create a Geometric Brownian Motion simulation.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            number_of_sims: Number of simulations to generate.</span>
@@ -464,7 +464,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Geometric Brownian Motion simulation.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">_validate_ar1_coef</span><span class="p">(</span><span class="n">ar1_coef</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">randomizer</span><span class="p">:</span>
             <span class="n">randomizer</span> <span class="o">=</span> <span class="n">_random_generator</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
@@ -480,7 +480,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
             <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">number_of_sims</span><span class="p">,</span> <span class="n">trading_days</span><span class="p">),</span>
         <span class="p">)</span>
 
-        <span class="n">returns_df</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">drift</span> <span class="o">+</span> <span class="n">wiener</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">)</span>
+        <span class="n">returns_df</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">drift</span> <span class="o">+</span> <span class="n">wiener</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">)</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="n">_apply_ar1_filter</span><span class="p">(</span><span class="n">returns_df</span><span class="p">,</span> <span class="n">ar1_coef</span><span class="p">)</span>
 
         <span class="k">return</span> <span class="n">_create_base_simulation</span><span class="p">(</span>
@@ -512,7 +512,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">randomizer</span><span class="p">:</span> <span class="n">Generator</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">ar1_coef</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ReturnSimulation</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a Merton Jump-Diffusion model simulation.</span>
+<span class="w">        </span><span class="sd">"""Create a Merton Jump-Diffusion model simulation.</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            number_of_sims: Number of simulations to generate.</span>
@@ -532,7 +532,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            Merton Jump-Diffusion model simulation.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">_validate_ar1_coef</span><span class="p">(</span><span class="n">ar1_coef</span><span class="p">)</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="n">randomizer</span><span class="p">:</span>
             <span class="n">randomizer</span> <span class="o">=</span> <span class="n">_random_generator</span><span class="p">(</span><span class="n">seed</span><span class="o">=</span><span class="n">seed</span><span class="p">)</span>
@@ -565,7 +565,7 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">raw_returns</span> <span class="o">=</span> <span class="n">poisson_jumps</span> <span class="o">+</span> <span class="n">drift</span> <span class="o">+</span> <span class="n">wiener</span>
         <span class="n">raw_returns</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.0</span>
 
-        <span class="n">returns_df</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">raw_returns</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float64&quot;</span><span class="p">)</span>
+        <span class="n">returns_df</span> <span class="o">=</span> <span class="n">DataFrame</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">raw_returns</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s2">"float64"</span><span class="p">)</span>
         <span class="n">returns</span> <span class="o">=</span> <span class="n">_apply_ar1_filter</span><span class="p">(</span><span class="n">returns_df</span><span class="p">,</span> <span class="n">ar1_coef</span><span class="p">)</span>
 
         <span class="k">return</span> <span class="n">_create_base_simulation</span><span class="p">(</span>
@@ -590,22 +590,22 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
         <span class="n">start</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">end</span><span class="p">:</span> <span class="n">dt</span><span class="o">.</span><span class="n">date</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">&quot;SE&quot;</span><span class="p">,</span>
+        <span class="n">countries</span><span class="p">:</span> <span class="n">CountriesType</span> <span class="o">=</span> <span class="s2">"SE"</span><span class="p">,</span>
         <span class="n">markets</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataFrame</span><span class="p">:</span>
-<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a pandas.DataFrame from simulation(s).</span>
+<span class="w">        </span><span class="sd">"""Create a pandas.DataFrame from simulation(s).</span>
 
 <span class="sd">        Args:</span>
 <span class="sd">            name: Name label of the serie(s).</span>
 <span class="sd">            start: Date when the simulation starts.</span>
 <span class="sd">            end: Date when the simulation ends.</span>
 <span class="sd">            countries: (List of) country code(s) according to ISO 3166-1 alpha-2.</span>
-<span class="sd">                Defaults to &quot;SE&quot;.</span>
+<span class="sd">                Defaults to "SE".</span>
 <span class="sd">            markets: (List of) markets code(s) supported by exchange_calendars.</span>
 
 <span class="sd">        Returns:</span>
 <span class="sd">            The simulation(s) data.</span>
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        """</span>
         <span class="n">d_range</span> <span class="o">=</span> <span class="n">generate_calendar_date_range</span><span class="p">(</span>
             <span class="n">trading_days</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">trading_days</span><span class="p">,</span>
             <span class="n">start</span><span class="o">=</span><span class="n">start</span><span class="p">,</span>
@@ -631,14 +631,14 @@ <h1>Source code for openseries.simulation</h1><div class="highlight"><pre>
                 <span class="n">index</span><span class="o">=</span><span class="n">Index</span><span class="p">(</span><span class="n">d_range</span><span class="p">),</span>
                 <span class="n">columns</span><span class="o">=</span><span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
                     <span class="p">[</span>
-                        <span class="p">[</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">_</span><span class="si">{</span><span class="n">item</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">],</span>
+                        <span class="p">[</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">_</span><span class="si">{</span><span class="n">item</span><span class="si">}</span><span class="s2">"</span><span class="p">],</span>
                         <span class="p">[</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">],</span>
                     <span class="p">],</span>
                 <span class="p">),</span>
             <span class="p">)</span>
             <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">number_of_sims</span><span class="p">)</span>
         <span class="p">]</span>
-        <span class="k">return</span> <span class="n">concat</span><span class="p">(</span><span class="n">df_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;columns&quot;</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">concat</span><span class="p">(</span><span class="n">df_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">"columns"</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
 </div>
 
 </pre></div>
diff --git a/docs/build/html/_sources/user_guide/installation.rst.txt b/docs/build/html/_sources/user_guide/installation.rst.txt
index 9561e284..3ae5fc99 100644
--- a/docs/build/html/_sources/user_guide/installation.rst.txt
+++ b/docs/build/html/_sources/user_guide/installation.rst.txt
@@ -52,7 +52,7 @@ Core Dependencies
 - **pandas** (>=2.1.2,<3.0.0) - Data manipulation and analysis
 - **numpy** (>=1.23.2,!=2.3.0,<3.0.0) - Numerical computing
 - **pydantic** (>=2.5.2,<3.0.0) - Data validation and settings management
-- **plotly** (>=5.18.0,<7.0.0) - Interactive plotting
+- **plotly** (>=5.18.0) - Interactive plotting
 - **scipy** (>=1.11.4,<2.0.0) - Scientific computing
 - **scikit-learn** (>=1.4.0,<2.0.0) - Machine learning utilities
 
diff --git a/docs/build/html/api/frame.html b/docs/build/html/api/frame.html
index 66beb084..746bffd1 100644
--- a/docs/build/html/api/frame.html
+++ b/docs/build/html/api/frame.html
@@ -221,7 +221,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 <dd class="field-even"><p>Properties of the constituent OpenTimeSeries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -441,7 +441,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 
 <dl class="py property">
 <dt class="sig sig-object py">
-<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">correl_matrix</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><span class="pre">DataFrame</span></a></span></dt>
+<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">correl_matrix</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><span class="pre">DataFrame</span></a></span></dt>
 <dd><p>Correlation matrix.</p>
 <p>This property returns the correlation matrix of the time series
 in the frame.</p>
@@ -730,7 +730,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 <dd class="field-even"><p>A basket timeseries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -760,7 +760,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 <dd class="field-even"><p>Rolling Information Ratios.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -788,7 +788,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 <dd class="field-even"><p>Rolling Betas.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -815,7 +815,7 @@ <h1>OpenFrame<a class="headerlink" href="#openframe" title="Link to this heading
 <dd class="field-even"><p>Rolling Correlations.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1115,7 +1115,7 @@ <h3>Financial Metrics<a class="headerlink" href="#financial-metrics" title="Link
 </ul>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-even"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1573,7 +1573,7 @@ <h3>Portfolio Analysis<a class="headerlink" href="#portfolio-analysis" title="Li
 <dd class="field-even"><p>A basket timeseries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1853,7 +1853,7 @@ <h3>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <dd class="field-even"><p>Rolling Information Ratios.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1881,7 +1881,7 @@ <h3>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <dd class="field-even"><p>Rolling Betas.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1908,7 +1908,7 @@ <h3>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <dd class="field-even"><p>Rolling Correlations.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1929,7 +1929,7 @@ <h3>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <dd class="field-even"><p>DataFrame with rolling returns.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1998,7 +1998,7 @@ <h3>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <dd class="field-even"><p>DataFrame with rolling annualized downside CVaR.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
diff --git a/docs/build/html/api/generated/openseries.OpenFrame.html b/docs/build/html/api/generated/openseries.OpenFrame.html
index 2c2909cf..d6cb48a8 100644
--- a/docs/build/html/api/generated/openseries.OpenFrame.html
+++ b/docs/build/html/api/generated/openseries.OpenFrame.html
@@ -631,7 +631,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 <dd class="field-even"><p>Properties of the constituent OpenTimeSeries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -851,7 +851,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 
 <dl class="py property">
 <dt class="sig sig-object py">
-<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">correl_matrix</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><span class="pre">DataFrame</span></a></span></dt>
+<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">correl_matrix</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><span class="pre">DataFrame</span></a></span></dt>
 <dd><p>Correlation matrix.</p>
 <p>This property returns the correlation matrix of the time series
 in the frame.</p>
@@ -1140,7 +1140,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 <dd class="field-even"><p>A basket timeseries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1170,7 +1170,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 <dd class="field-even"><p>Rolling Information Ratios.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1198,7 +1198,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 <dd class="field-even"><p>Rolling Betas.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1225,7 +1225,7 @@ <h1>openseries.OpenFrame<a class="headerlink" href="#openseries-openframe" title
 <dd class="field-even"><p>Rolling Correlations.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
diff --git a/docs/build/html/api/generated/openseries.OpenTimeSeries.html b/docs/build/html/api/generated/openseries.OpenTimeSeries.html
index e300bd60..266052e2 100644
--- a/docs/build/html/api/generated/openseries.OpenTimeSeries.html
+++ b/docs/build/html/api/generated/openseries.OpenTimeSeries.html
@@ -146,7 +146,7 @@ <h1>openseries.OpenTimeSeries<a class="headerlink" href="#openseries-opentimeser
 <li><p><strong>values</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.14)"><em>list</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>]</em><em>, </em><em>MinLen</em><em>(</em><em>min_length=1</em><em>)</em><em>]</em>) – The value or return values of the timeseries items.
 These values will not be altered by methods.</p></li>
 <li><p><strong>local_ccy</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Boolean flag indicating if timeseries is in local currency.</p></li>
-<li><p><strong>tsdf</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a>) – Pandas object holding dates and values that can be altered via
+<li><p><strong>tsdf</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a>) – Pandas object holding dates and values that can be altered via
 methods.</p></li>
 <li><p><strong>currency</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.14)"><em>str</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.StringConstraints" title="(in Pydantic v0.0.0)"><em>StringConstraints</em></a><em>(</em><em>strip_whitespace=True</em><em>, </em><em>to_upper=True</em><em>, </em><em>to_lower=None</em><em>, </em><em>strict=True</em><em>, </em><em>min_length=3</em><em>, </em><em>max_length=3</em><em>, </em><em>pattern=^</em><em>[</em><em>A-Z</em><em>]</em><em>{3}$</em><em>, </em><em>ascii_only=None</em><em>)</em><em>]</em>) – ISO 4217 currency code of the timeseries.</p></li>
 <li><p><strong>domestic</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.14)"><em>str</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.StringConstraints" title="(in Pydantic v0.0.0)"><em>StringConstraints</em></a><em>(</em><em>strip_whitespace=True</em><em>, </em><em>to_upper=True</em><em>, </em><em>to_lower=None</em><em>, </em><em>strict=True</em><em>, </em><em>min_length=3</em><em>, </em><em>max_length=3</em><em>, </em><em>pattern=^</em><em>[</em><em>A-Z</em><em>]</em><em>{3}$</em><em>, </em><em>ascii_only=None</em><em>)</em><em>]</em>) – ISO 4217 currency code of the user’s home currency.
@@ -678,7 +678,7 @@ <h1>openseries.OpenTimeSeries<a class="headerlink" href="#openseries-opentimeser
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.3)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.5)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
 <li><p><strong>column_nmbr</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a>) – Using iloc[:, column_nmbr] to pick column. Defaults to 0.</p></li>
 <li><p><strong>valuetype</strong> (<em>ValueType</em>) – Identifies if the series is a series of values or returns.
 Defaults to ValueType.PRICE.</p></li>
@@ -710,7 +710,7 @@ <h1>openseries.OpenTimeSeries<a class="headerlink" href="#openseries-opentimeser
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>rate</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – The accrual rate.</p></li>
-<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.3)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
+<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.5)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
 <li><p><strong>days</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Number of days to generate when date_range not provided. Must be
 combined with end_dt. Optional.</p></li>
 <li><p><strong>end_dt</strong> (<a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.date" title="(in Python v3.14)"><em>date</em></a><em> | </em><em>None</em>) – End date of date range to generate when date_range not provided.
@@ -786,7 +786,7 @@ <h1>openseries.OpenTimeSeries<a class="headerlink" href="#openseries-opentimeser
 <dd class="field-even"><p>Properties of the OpenTimeSeries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
diff --git a/docs/build/html/api/generated/openseries.ReturnSimulation.html b/docs/build/html/api/generated/openseries.ReturnSimulation.html
index 6e8da5dd..45006040 100644
--- a/docs/build/html/api/generated/openseries.ReturnSimulation.html
+++ b/docs/build/html/api/generated/openseries.ReturnSimulation.html
@@ -138,7 +138,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.Strict" title="(in Pydantic v0.0.0)"><em>Strict</em></a><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em>) – Number of trading days used to annualize.</p></li>
 <li><p><strong>mean_annual_return</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Mean annual return of the distribution.</p></li>
 <li><p><strong>mean_annual_vol</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Gt</em><em>(</em><em>gt=0</em><em>)</em><em>]</em>) – Mean annual standard deviation of the distribution.</p></li>
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
 <li><p><strong>jumps_lamda</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the probability of a jump happening at each point in time.
 Defaults to 0.0.</p></li>
 <li><p><strong>jumps_sigma</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the volatility of the jump size. Defaults to 0.0.</p></li>
@@ -373,7 +373,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 
 <dl class="py property">
 <dt class="sig sig-object py">
-<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
+<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
 <dd><p>Simulation data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
@@ -418,7 +418,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -446,7 +446,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -474,7 +474,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -506,7 +506,7 @@ <h1>openseries.ReturnSimulation<a class="headerlink" href="#openseries-returnsim
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
diff --git a/docs/build/html/api/series.html b/docs/build/html/api/series.html
index 34ac24c9..f5f08f88 100644
--- a/docs/build/html/api/series.html
+++ b/docs/build/html/api/series.html
@@ -151,7 +151,7 @@ <h1>OpenTimeSeries<a class="headerlink" href="#opentimeseries" title="Link to th
 <li><p><strong>values</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.14)"><em>list</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>]</em><em>, </em><em>MinLen</em><em>(</em><em>min_length=1</em><em>)</em><em>]</em>) – The value or return values of the timeseries items.
 These values will not be altered by methods.</p></li>
 <li><p><strong>local_ccy</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.14)"><em>bool</em></a>) – Boolean flag indicating if timeseries is in local currency.</p></li>
-<li><p><strong>tsdf</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a>) – Pandas object holding dates and values that can be altered via
+<li><p><strong>tsdf</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a>) – Pandas object holding dates and values that can be altered via
 methods.</p></li>
 <li><p><strong>currency</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.14)"><em>str</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.StringConstraints" title="(in Pydantic v0.0.0)"><em>StringConstraints</em></a><em>(</em><em>strip_whitespace=True</em><em>, </em><em>to_upper=True</em><em>, </em><em>to_lower=None</em><em>, </em><em>strict=True</em><em>, </em><em>min_length=3</em><em>, </em><em>max_length=3</em><em>, </em><em>pattern=^</em><em>[</em><em>A-Z</em><em>]</em><em>{3}$</em><em>, </em><em>ascii_only=None</em><em>)</em><em>]</em>) – ISO 4217 currency code of the timeseries.</p></li>
 <li><p><strong>domestic</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.14)"><em>str</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.StringConstraints" title="(in Pydantic v0.0.0)"><em>StringConstraints</em></a><em>(</em><em>strip_whitespace=True</em><em>, </em><em>to_upper=True</em><em>, </em><em>to_lower=None</em><em>, </em><em>strict=True</em><em>, </em><em>min_length=3</em><em>, </em><em>max_length=3</em><em>, </em><em>pattern=^</em><em>[</em><em>A-Z</em><em>]</em><em>{3}$</em><em>, </em><em>ascii_only=None</em><em>)</em><em>]</em>) – ISO 4217 currency code of the user’s home currency.
@@ -269,7 +269,7 @@ <h1>OpenTimeSeries<a class="headerlink" href="#opentimeseries" title="Link to th
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.3)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.5)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
 <li><p><strong>column_nmbr</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a>) – Using iloc[:, column_nmbr] to pick column. Defaults to 0.</p></li>
 <li><p><strong>valuetype</strong> (<em>ValueType</em>) – Identifies if the series is a series of values or returns.
 Defaults to ValueType.PRICE.</p></li>
@@ -301,7 +301,7 @@ <h1>OpenTimeSeries<a class="headerlink" href="#opentimeseries" title="Link to th
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>rate</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – The accrual rate.</p></li>
-<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.3)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
+<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.5)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
 <li><p><strong>days</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Number of days to generate when date_range not provided. Must be
 combined with end_dt. Optional.</p></li>
 <li><p><strong>end_dt</strong> (<a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.date" title="(in Python v3.14)"><em>date</em></a><em> | </em><em>None</em>) – End date of date range to generate when date_range not provided.
@@ -377,7 +377,7 @@ <h1>OpenTimeSeries<a class="headerlink" href="#opentimeseries" title="Link to th
 <dd class="field-even"><p>Properties of the OpenTimeSeries.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -762,7 +762,7 @@ <h2>Class Methods for Construction<a class="headerlink" href="#class-methods-for
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.3)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v3.0.5)"><em>Series</em></a><em> | </em><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a><em> | </em><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.14)"><em>object</em></a>) – Pandas DataFrame or Series.</p></li>
 <li><p><strong>column_nmbr</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a>) – Using iloc[:, column_nmbr] to pick column. Defaults to 0.</p></li>
 <li><p><strong>valuetype</strong> (<em>ValueType</em>) – Identifies if the series is a series of values or returns.
 Defaults to ValueType.PRICE.</p></li>
@@ -794,7 +794,7 @@ <h2>Class Methods for Construction<a class="headerlink" href="#class-methods-for
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>rate</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – The accrual rate.</p></li>
-<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.3)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
+<li><p><strong>d_range</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DatetimeIndex.html#pandas.DatetimeIndex" title="(in pandas v3.0.5)"><em>DatetimeIndex</em></a><em> | </em><em>None</em>) – A given range of dates. Optional.</p></li>
 <li><p><strong>days</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Number of days to generate when date_range not provided. Must be
 combined with end_dt. Optional.</p></li>
 <li><p><strong>end_dt</strong> (<a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.date" title="(in Python v3.14)"><em>date</em></a><em> | </em><em>None</em>) – End date of date range to generate when date_range not provided.
@@ -1009,7 +1009,7 @@ <h3>Financial Metrics<a class="headerlink" href="#financial-metrics" title="Link
 </ul>
 </dd>
 <dt class="field-even">Return type<span class="colon">:</span></dt>
-<dd class="field-even"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-even"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1832,7 +1832,7 @@ <h3>Analysis Methods<a class="headerlink" href="#analysis-methods" title="Link t
 <dd class="field-even"><p>DataFrame with rolling returns.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -1901,7 +1901,7 @@ <h3>Analysis Methods<a class="headerlink" href="#analysis-methods" title="Link t
 <dd class="field-even"><p>DataFrame with rolling annualized downside CVaR.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a></p>
 </dd>
 </dl>
 </dd></dl>
diff --git a/docs/build/html/api/simulation.html b/docs/build/html/api/simulation.html
index 2e0cb61d..13f94e91 100644
--- a/docs/build/html/api/simulation.html
+++ b/docs/build/html/api/simulation.html
@@ -129,7 +129,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.Strict" title="(in Pydantic v0.0.0)"><em>Strict</em></a><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em>) – Number of trading days used to annualize.</p></li>
 <li><p><strong>mean_annual_return</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Mean annual return of the distribution.</p></li>
 <li><p><strong>mean_annual_vol</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Gt</em><em>(</em><em>gt=0</em><em>)</em><em>]</em>) – Mean annual standard deviation of the distribution.</p></li>
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
 <li><p><strong>jumps_lamda</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the probability of a jump happening at each point in time.
 Defaults to 0.0.</p></li>
 <li><p><strong>jumps_sigma</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the volatility of the jump size. Defaults to 0.0.</p></li>
@@ -196,7 +196,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 
 <dl class="py property">
 <dt class="sig sig-object py">
-<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
+<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
 <dd><p>Simulation data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
@@ -241,7 +241,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -269,7 +269,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -297,7 +297,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -329,7 +329,7 @@ <h1>Simulation<a class="headerlink" href="#simulation" title="Link to this headi
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -385,7 +385,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><a class="reference external" href="https://pydantic.dev/docs/validation/latest/api/pydantic/types/#pydantic.types.Strict" title="(in Pydantic v0.0.0)"><em>Strict</em></a><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em>) – Number of trading days used to annualize.</p></li>
 <li><p><strong>mean_annual_return</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Mean annual return of the distribution.</p></li>
 <li><p><strong>mean_annual_vol</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Gt</em><em>(</em><em>gt=0</em><em>)</em><em>]</em>) – Mean annual standard deviation of the distribution.</p></li>
-<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
+<li><p><strong>dframe</strong> (<a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><em>DataFrame</em></a>) – Pandas DataFrame object holding the resulting values.</p></li>
 <li><p><strong>jumps_lamda</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the probability of a jump happening at each point in time.
 Defaults to 0.0.</p></li>
 <li><p><strong>jumps_sigma</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a><em>, </em><em>Ge</em><em>(</em><em>ge=0</em><em>)</em><em>]</em>) – This is the volatility of the jump size. Defaults to 0.0.</p></li>
@@ -452,7 +452,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 
 <dl class="py property">
 <dt class="sig sig-object py">
-<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.3)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
+<span class="property"><span class="k"><span class="pre">property</span></span><span class="w"> </span></span><span class="sig-name descname"><span class="pre">results</span></span><span class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.5)"><span class="pre">DataFrame</span></a></span><a class="reference internal" href="../_modules/openseries/simulation.html#ReturnSimulation.results"><span class="viewcode-link"><span class="pre">[source]</span></span></a></dt>
 <dd><p>Simulation data.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns<span class="colon">:</span></dt>
@@ -497,7 +497,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -525,7 +525,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -553,7 +553,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
@@ -585,7 +585,7 @@ <h2>ReturnSimulation Class<a class="headerlink" href="#returnsimulation-class" t
 <li><p><strong>trading_days_in_year</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Annotated" title="(in Python v3.14)"><em>Annotated</em></a><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em>, </em><em>FieldInfo</em><em>(</em><em>annotation=NoneType</em><em>, </em><em>required=True</em><em>, </em><em>metadata=</em><em>[</em><em>Strict</em><em>(</em><em>strict=True</em><em>)</em><em>, </em><em>Ge</em><em>(</em><em>ge=1</em><em>)</em><em>, </em><em>Le</em><em>(</em><em>le=366</em><em>)</em><em>]</em><em>)</em><em>]</em>) – Number of trading days used to annualize.
 Defaults to 252.</p></li>
 <li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.14)"><em>int</em></a><em> | </em><em>None</em>) – Seed for random process initiation.</p></li>
-<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.4)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
+<li><p><strong>randomizer</strong> (<a class="reference external" href="https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.Generator" title="(in NumPy v2.5)"><em>Generator</em></a><em> | </em><em>None</em>) – Random process generator.</p></li>
 <li><p><strong>ar1_coef</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.14)"><em>float</em></a>) – Lag-1 autoregressive coefficient in (-1, 1) to induce
 autocorrelation. Defaults to 0.0 (i.i.d. returns).</p></li>
 </ul>
diff --git a/docs/build/html/api/types.html b/docs/build/html/api/types.html
index e28cf820..b1603da1 100644
--- a/docs/build/html/api/types.html
+++ b/docs/build/html/api/types.html
@@ -290,10 +290,10 @@ <h2>Type Aliases<a class="headerlink" href="#type-aliases" title="Link to this h
 </div></blockquote>
 <p>However, if desired, reusable type variables can also be constructed
 manually, like so:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span>  <span class="c1"># Can be anything</span>
-<span class="n">S</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">&#39;S&#39;</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>  <span class="c1"># Can be any subtype of str</span>
-<span class="n">A</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">&#39;A&#39;</span><span class="p">,</span> <span class="nb">str</span><span class="p">,</span> <span class="nb">bytes</span><span class="p">)</span>  <span class="c1"># Must be exactly str or bytes</span>
-<span class="n">D</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">&#39;D&#39;</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>  <span class="c1"># Defaults to int</span>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">'T'</span><span class="p">)</span>  <span class="c1"># Can be anything</span>
+<span class="n">S</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">'S'</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span>  <span class="c1"># Can be any subtype of str</span>
+<span class="n">A</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">'A'</span><span class="p">,</span> <span class="nb">str</span><span class="p">,</span> <span class="nb">bytes</span><span class="p">)</span>  <span class="c1"># Must be exactly str or bytes</span>
+<span class="n">D</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">'D'</span><span class="p">,</span> <span class="n">default</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>  <span class="c1"># Defaults to int</span>
 </pre></div>
 </div>
 <p>Type variables exist primarily for the benefit of static type
diff --git a/docs/build/html/development/contributing.html b/docs/build/html/development/contributing.html
index 7295d67e..8c39048b 100644
--- a/docs/build/html/development/contributing.html
+++ b/docs/build/html/development/contributing.html
@@ -182,7 +182,7 @@ <h3>Development Setup<a class="headerlink" href="#development-setup" title="Link
 </ol>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>uv<span class="w"> </span>venv<span class="w"> </span>venv
 <span class="nb">source</span><span class="w"> </span>venv/bin/activate
-uv<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span><span class="s2">&quot;.[dev,docs]&quot;</span>
+uv<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span><span class="s2">".[dev,docs]"</span>
 </pre></div>
 </div>
 <ol class="arabic simple" start="5">
@@ -217,7 +217,7 @@ <h3>Development Workflow<a class="headerlink" href="#development-workflow" title
 <li><p>Commit your changes:</p></li>
 </ol>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>add<span class="w"> </span>.
-git<span class="w"> </span>commit<span class="w"> </span>-m<span class="w"> </span><span class="s2">&quot;Add your descriptive commit message&quot;</span>
+git<span class="w"> </span>commit<span class="w"> </span>-m<span class="w"> </span><span class="s2">"Add your descriptive commit message"</span>
 </pre></div>
 </div>
 <ol class="arabic simple" start="6">
@@ -247,7 +247,7 @@ <h3>Code Style<a class="headerlink" href="#code-style" title="Link to this headi
 <h3>Type Hints<a class="headerlink" href="#type-hints" title="Link to this heading"></a></h3>
 <p>All new code should include proper type hints:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">calculate_returns</span><span class="p">(</span><span class="n">prices</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]:</span>
-<span class="w">     </span><span class="sd">&quot;&quot;&quot;Calculate simple returns from prices.&quot;&quot;&quot;</span>
+<span class="w">     </span><span class="sd">"""Calculate simple returns from prices."""</span>
      <span class="n">returns</span> <span class="o">=</span> <span class="p">[]</span>
      <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">prices</span><span class="p">)):</span>
           <span class="n">ret</span> <span class="o">=</span> <span class="p">(</span><span class="n">prices</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">/</span> <span class="n">prices</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="o">-</span> <span class="mi">1</span>
@@ -260,7 +260,7 @@ <h3>Type Hints<a class="headerlink" href="#type-hints" title="Link to this headi
 <h3>Docstrings<a class="headerlink" href="#docstrings" title="Link to this heading"></a></h3>
 <p>Use Google-style docstrings for all public functions and classes:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">calculate_sharpe_ratio</span><span class="p">(</span><span class="n">returns</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">],</span> <span class="n">risk_free_rate</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-<span class="w">     </span><span class="sd">&quot;&quot;&quot;Calculate the Sharpe ratio.</span>
+<span class="w">     </span><span class="sd">"""Calculate the Sharpe ratio.</span>
 
 <span class="sd">     Args:</span>
 <span class="sd">          returns: List of periodic returns.</span>
@@ -275,10 +275,10 @@ <h3>Docstrings<a class="headerlink" href="#docstrings" title="Link to this headi
 <span class="sd">     Example:</span>
 <span class="sd">          &gt;&gt;&gt; returns = [0.01, 0.02, -0.01, 0.03]</span>
 <span class="sd">          &gt;&gt;&gt; sharpe = calculate_sharpe_ratio(returns)</span>
-<span class="sd">          &gt;&gt;&gt; print(f&quot;Sharpe ratio: {sharpe:.3f}&quot;)</span>
-<span class="sd">     &quot;&quot;&quot;</span>
+<span class="sd">          &gt;&gt;&gt; print(f"Sharpe ratio: {sharpe:.3f}")</span>
+<span class="sd">     """</span>
      <span class="k">if</span> <span class="ow">not</span> <span class="n">returns</span><span class="p">:</span>
-          <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Returns list cannot be empty&quot;</span><span class="p">)</span>
+          <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Returns list cannot be empty"</span><span class="p">)</span>
 
      <span class="n">mean_return</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">returns</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">returns</span><span class="p">)</span>
      <span class="n">std_dev</span> <span class="o">=</span> <span class="p">(</span><span class="nb">sum</span><span class="p">((</span><span class="n">r</span> <span class="o">-</span> <span class="n">mean_return</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="n">returns</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">returns</span><span class="p">))</span> <span class="o">**</span> <span class="mf">0.5</span>
@@ -314,57 +314,57 @@ <h3>Writing Tests<a class="headerlink" href="#writing-tests" title="Link to this
 <span class="kn">from</span><span class="w"> </span><span class="nn">openseries</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenTimeSeries</span>
 
 <span class="k">class</span><span class="w"> </span><span class="nc">TestOpenTimeSeries</span><span class="p">:</span>
-<span class="w">     </span><span class="sd">&quot;&quot;&quot;Test cases for OpenTimeSeries class.&quot;&quot;&quot;</span>
+<span class="w">     </span><span class="sd">"""Test cases for OpenTimeSeries class."""</span>
 
      <span class="k">def</span><span class="w"> </span><span class="nf">test_from_arrays_basic</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-<span class="w">          </span><span class="sd">&quot;&quot;&quot;Test basic creation from arrays.&quot;&quot;&quot;</span>
-          <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">]</span>
+<span class="w">          </span><span class="sd">"""Test basic creation from arrays."""</span>
+          <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">]</span>
           <span class="n">values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">,</span> <span class="mf">99.0</span><span class="p">]</span>
 
-          <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Test&quot;</span><span class="p">)</span>
+          <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Test"</span><span class="p">)</span>
 
-          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span> <span class="o">!=</span> <span class="s2">&quot;Test&quot;</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Expected name &#39;Test&#39;, got &#39;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">&#39;&quot;</span>
+          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span> <span class="o">!=</span> <span class="s2">"Test"</span><span class="p">:</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Expected name 'Test', got '</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">'"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
           <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">length</span> <span class="o">!=</span> <span class="mi">3</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Expected length 3, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Expected length 3, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
-          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">first_idx</span> <span class="o">!=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">date</span><span class="p">():</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Expected first_idx 2023-01-01, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">&quot;</span>
+          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">first_idx</span> <span class="o">!=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s1">'2023-01-01'</span><span class="p">)</span><span class="o">.</span><span class="n">date</span><span class="p">():</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Expected first_idx 2023-01-01, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
-          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">last_idx</span> <span class="o">!=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s1">&#39;2023-01-03&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">date</span><span class="p">():</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Expected last_idx 2023-01-03, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span>
+          <span class="k">if</span> <span class="n">series</span><span class="o">.</span><span class="n">last_idx</span> <span class="o">!=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Timestamp</span><span class="p">(</span><span class="s1">'2023-01-03'</span><span class="p">)</span><span class="o">.</span><span class="n">date</span><span class="p">():</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Expected last_idx 2023-01-03, got </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 
      <span class="k">def</span><span class="w"> </span><span class="nf">test_from_arrays_invalid_dates</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-<span class="w">          </span><span class="sd">&quot;&quot;&quot;Test that invalid dates raise appropriate errors.&quot;&quot;&quot;</span>
+<span class="w">          </span><span class="sd">"""Test that invalid dates raise appropriate errors."""</span>
           <span class="k">with</span> <span class="n">pytest</span><span class="o">.</span><span class="n">raises</span><span class="p">(</span><span class="ne">ValueError</span><span class="p">):</span>
                 <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-                     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;invalid-date&#39;</span><span class="p">],</span>
+                     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'invalid-date'</span><span class="p">],</span>
                      <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mf">100.0</span><span class="p">],</span>
-                     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Test&quot;</span>
+                     <span class="n">name</span><span class="o">=</span><span class="s2">"Test"</span>
                 <span class="p">)</span>
 
      <span class="k">def</span><span class="w"> </span><span class="nf">test_calculate_returns</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-<span class="w">          </span><span class="sd">&quot;&quot;&quot;Test return calculation.&quot;&quot;&quot;</span>
-          <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">]</span>
+<span class="w">          </span><span class="sd">"""Test return calculation."""</span>
+          <span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">]</span>
           <span class="n">values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">,</span> <span class="mf">99.0</span><span class="p">]</span>
 
-          <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Test&quot;</span><span class="p">)</span>
+          <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Test"</span><span class="p">)</span>
           <span class="n">series</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>  <span class="c1"># Modifies original</span>
 
           <span class="n">expected_returns</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.02</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.0294117647</span><span class="p">]</span>  <span class="c1"># Approximate</span>
           <span class="n">actual_returns</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">values</span>
 
           <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">actual_returns</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">2</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Expected 2 returns, got </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">actual_returns</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Expected 2 returns, got </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">actual_returns</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
           <span class="c1"># Use tolerance-based comparison</span>
           <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">expected_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">1e-6</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;First return mismatch: </span><span class="si">{</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">expected_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"First return mismatch: </span><span class="si">{</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">expected_returns</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
           <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">expected_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> <span class="o">&gt;=</span> <span class="mf">1e-6</span><span class="p">:</span>
-                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Second return mismatch: </span><span class="si">{</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">expected_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span>
+                <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"Second return mismatch: </span><span class="si">{</span><span class="n">actual_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">expected_returns</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span>
                 <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -511,11 +511,11 @@ <h3>IDE Setup<a class="headerlink" href="#ide-setup" title="Link to this heading
 </ul>
 <p>Recommended settings in <code class="docutils literal notranslate"><span class="pre">.vscode/settings.json</span></code>:</p>
 <div class="highlight-json notranslate"><div class="highlight"><pre><span></span><span class="p">{</span>
-<span class="w">    </span><span class="nt">&quot;python.defaultInterpreterPath&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;.venv/bin/python&quot;</span><span class="p">,</span>
-<span class="w">    </span><span class="nt">&quot;python.linting.enabled&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
-<span class="w">    </span><span class="nt">&quot;python.linting.ruffEnabled&quot;</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
-<span class="w">    </span><span class="nt">&quot;python.formatting.provider&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;ruff&quot;</span><span class="p">,</span>
-<span class="w">    </span><span class="nt">&quot;python.typeChecking&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;strict&quot;</span>
+<span class="w">    </span><span class="nt">"python.defaultInterpreterPath"</span><span class="p">:</span><span class="w"> </span><span class="s2">".venv/bin/python"</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">"python.linting.enabled"</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">"python.linting.ruffEnabled"</span><span class="p">:</span><span class="w"> </span><span class="kc">true</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">"python.formatting.provider"</span><span class="p">:</span><span class="w"> </span><span class="s2">"ruff"</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">"python.typeChecking"</span><span class="p">:</span><span class="w"> </span><span class="s2">"strict"</span>
 <span class="p">}</span>
 </pre></div>
 </div>
@@ -528,22 +528,22 @@ <h3>Debugging<a class="headerlink" href="#debugging" title="Link to this heading
 </div>
 <p>For debugging with VS Code, create <code class="docutils literal notranslate"><span class="pre">.vscode/launch.json</span></code>:</p>
 <div class="highlight-json notranslate"><div class="highlight"><pre><span></span><span class="p">{</span>
-<span class="w">    </span><span class="nt">&quot;version&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;0.2.0&quot;</span><span class="p">,</span>
-<span class="w">    </span><span class="nt">&quot;configurations&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
+<span class="w">    </span><span class="nt">"version"</span><span class="p">:</span><span class="w"> </span><span class="s2">"0.2.0"</span><span class="p">,</span>
+<span class="w">    </span><span class="nt">"configurations"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span>
 <span class="w">        </span><span class="p">{</span>
-<span class="w">            </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Python: Current File&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;python&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;request&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;launch&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;program&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;${file}&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;console&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;integratedTerminal&quot;</span>
+<span class="w">            </span><span class="nt">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"Python: Current File"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"python"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"request"</span><span class="p">:</span><span class="w"> </span><span class="s2">"launch"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"program"</span><span class="p">:</span><span class="w"> </span><span class="s2">"${file}"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"console"</span><span class="p">:</span><span class="w"> </span><span class="s2">"integratedTerminal"</span>
 <span class="w">        </span><span class="p">},</span>
 <span class="w">        </span><span class="p">{</span>
-<span class="w">            </span><span class="nt">&quot;name&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;Python: Pytest&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;type&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;python&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;request&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;launch&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;module&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;pytest&quot;</span><span class="p">,</span>
-<span class="w">            </span><span class="nt">&quot;args&quot;</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">&quot;${workspaceFolder}/tests&quot;</span><span class="p">],</span>
-<span class="w">            </span><span class="nt">&quot;console&quot;</span><span class="p">:</span><span class="w"> </span><span class="s2">&quot;integratedTerminal&quot;</span>
+<span class="w">            </span><span class="nt">"name"</span><span class="p">:</span><span class="w"> </span><span class="s2">"Python: Pytest"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"type"</span><span class="p">:</span><span class="w"> </span><span class="s2">"python"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"request"</span><span class="p">:</span><span class="w"> </span><span class="s2">"launch"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"module"</span><span class="p">:</span><span class="w"> </span><span class="s2">"pytest"</span><span class="p">,</span>
+<span class="w">            </span><span class="nt">"args"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">"${workspaceFolder}/tests"</span><span class="p">],</span>
+<span class="w">            </span><span class="nt">"console"</span><span class="p">:</span><span class="w"> </span><span class="s2">"integratedTerminal"</span>
 <span class="w">        </span><span class="p">}</span>
 <span class="w">    </span><span class="p">]</span>
 <span class="p">}</span>
diff --git a/docs/build/html/examples/custom_reports.html b/docs/build/html/examples/custom_reports.html
index ed8710c0..e4bb496a 100644
--- a/docs/build/html/examples/custom_reports.html
+++ b/docs/build/html/examples/custom_reports.html
@@ -124,13 +124,13 @@ <h2>Using the Built-in HTML Report<a class="headerlink" href="#using-the-built-i
 <span class="kn">import</span><span class="w"> </span><span class="nn">pandas</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">pd</span>
 
 <span class="c1"># Load sample data for comparison</span>
-<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="s2">&quot;MSFT&quot;</span><span class="p">,</span> <span class="s2">&quot;GOOGL&quot;</span><span class="p">,</span> <span class="s2">&quot;SPY&quot;</span><span class="p">]</span>
-<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;Apple&quot;</span><span class="p">,</span> <span class="s2">&quot;Microsoft&quot;</span><span class="p">,</span> <span class="s2">&quot;Google&quot;</span><span class="p">,</span> <span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">]</span>
+<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"AAPL"</span><span class="p">,</span> <span class="s2">"MSFT"</span><span class="p">,</span> <span class="s2">"GOOGL"</span><span class="p">,</span> <span class="s2">"SPY"</span><span class="p">]</span>
+<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"Apple"</span><span class="p">,</span> <span class="s2">"Microsoft"</span><span class="p">,</span> <span class="s2">"Google"</span><span class="p">,</span> <span class="s2">"S&amp;P 500"</span><span class="p">]</span>
 
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">tickers</span><span class="p">,</span> <span class="n">names</span><span class="p">):</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
@@ -141,12 +141,12 @@ <h2>Using the Built-in HTML Report<a class="headerlink" href="#using-the-built-i
 <span class="c1"># The last asset in the frame is used as the benchmark</span>
 <span class="n">figure</span><span class="p">,</span> <span class="n">filepath</span> <span class="o">=</span> <span class="n">report_html</span><span class="p">(</span>
      <span class="n">data</span><span class="o">=</span><span class="n">comparison_frame</span><span class="p">,</span>
-     <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;file&quot;</span><span class="p">,</span>
-     <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;stock_comparison_report.html&quot;</span>
+     <span class="n">output_type</span><span class="o">=</span><span class="s2">"file"</span><span class="p">,</span>
+     <span class="n">filename</span><span class="o">=</span><span class="s2">"stock_comparison_report.html"</span>
 <span class="p">)</span>
 
 <span class="c1"># filepath contains the path to the saved HTML file</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Report saved to: </span><span class="si">{</span><span class="n">filepath</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Report saved to: </span><span class="si">{</span><span class="n">filepath</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># The figure object can be used for further customization if needed</span>
 <span class="c1"># figure.show()  # Display the figure interactively</span>
@@ -159,7 +159,7 @@ <h2>Embedding Reports in Existing HTML Pages<a class="headerlink" href="#embeddi
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Generate HTML div section for embedding</span>
 <span class="n">figure</span><span class="p">,</span> <span class="n">html_div</span> <span class="o">=</span> <span class="n">report_html</span><span class="p">(</span>
      <span class="n">data</span><span class="o">=</span><span class="n">comparison_frame</span><span class="p">,</span>
-     <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;div&quot;</span>
+     <span class="n">output_type</span><span class="o">=</span><span class="s2">"div"</span>
 <span class="p">)</span>
 
 <span class="c1"># html_div contains the responsive HTML div section</span>
@@ -167,7 +167,7 @@ <h2>Embedding Reports in Existing HTML Pages<a class="headerlink" href="#embeddi
 <span class="c1"># It includes both desktop and mobile layouts with CSS and JavaScript</span>
 
 <span class="c1"># Example: Save to a custom HTML template</span>
-<span class="n">html_template</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;&quot;&quot;</span>
+<span class="n">html_template</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"""</span>
 <span class="s2">&lt;!DOCTYPE html&gt;</span>
 <span class="s2">&lt;html&gt;</span>
 <span class="s2">&lt;head&gt;</span>
@@ -178,9 +178,9 @@ <h2>Embedding Reports in Existing HTML Pages<a class="headerlink" href="#embeddi
 <span class="s2">    </span><span class="si">{</span><span class="n">html_div</span><span class="si">}</span>
 <span class="s2">&lt;/body&gt;</span>
 <span class="s2">&lt;/html&gt;</span>
-<span class="s2">&quot;&quot;&quot;</span>
+<span class="s2">"""</span>
 
-<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;custom_report.html&quot;</span><span class="p">,</span> <span class="s2">&quot;w&quot;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
+<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">"custom_report.html"</span><span class="p">,</span> <span class="s2">"w"</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s2">"utf-8"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
     <span class="n">f</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">html_template</span><span class="p">)</span>
 </pre></div>
 </div>
diff --git a/docs/build/html/examples/multi_asset.html b/docs/build/html/examples/multi_asset.html
index a1d6a64b..6c574967 100644
--- a/docs/build/html/examples/multi_asset.html
+++ b/docs/build/html/examples/multi_asset.html
@@ -133,32 +133,32 @@ <h2>Setting Up Multi-Asset Analysis<a class="headerlink" href="#setting-up-multi
 
 <span class="c1"># Define asset universe</span>
 <span class="n">assets</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;AAPL&quot;</span><span class="p">:</span> <span class="s2">&quot;Apple Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;GOOGL&quot;</span><span class="p">:</span> <span class="s2">&quot;Alphabet Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;MSFT&quot;</span><span class="p">:</span> <span class="s2">&quot;Microsoft Corp.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;AMZN&quot;</span><span class="p">:</span> <span class="s2">&quot;Amazon.com Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;TSLA&quot;</span><span class="p">:</span> <span class="s2">&quot;Tesla Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;NVDA&quot;</span><span class="p">:</span> <span class="s2">&quot;NVIDIA Corp.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;META&quot;</span><span class="p">:</span> <span class="s2">&quot;Meta Platforms Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;NFLX&quot;</span><span class="p">:</span> <span class="s2">&quot;Netflix Inc.&quot;</span>
+     <span class="s2">"AAPL"</span><span class="p">:</span> <span class="s2">"Apple Inc."</span><span class="p">,</span>
+     <span class="s2">"GOOGL"</span><span class="p">:</span> <span class="s2">"Alphabet Inc."</span><span class="p">,</span>
+     <span class="s2">"MSFT"</span><span class="p">:</span> <span class="s2">"Microsoft Corp."</span><span class="p">,</span>
+     <span class="s2">"AMZN"</span><span class="p">:</span> <span class="s2">"Amazon.com Inc."</span><span class="p">,</span>
+     <span class="s2">"TSLA"</span><span class="p">:</span> <span class="s2">"Tesla Inc."</span><span class="p">,</span>
+     <span class="s2">"NVDA"</span><span class="p">:</span> <span class="s2">"NVIDIA Corp."</span><span class="p">,</span>
+     <span class="s2">"META"</span><span class="p">:</span> <span class="s2">"Meta Platforms Inc."</span><span class="p">,</span>
+     <span class="s2">"NFLX"</span><span class="p">:</span> <span class="s2">"Netflix Inc."</span>
 <span class="p">}</span>
 
 <span class="c1"># Download data for all assets</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">assets</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
      <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
      <span class="p">)</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenFrame</span>
 <span class="n">tech_stocks</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">series_list</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Created frame with </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Common period: </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Created frame with </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Common period: </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -166,18 +166,18 @@ <h2>Setting Up Multi-Asset Analysis<a class="headerlink" href="#setting-up-multi
 <h2>Comparative Analysis<a class="headerlink" href="#comparative-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Get metrics for all assets</span>
 <span class="n">all_metrics</span> <span class="o">=</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== COMPARATIVE METRICS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== COMPARATIVE METRICS ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">all_metrics</span><span class="p">)</span>
 
 <span class="c1"># Focus on key metrics</span>
-<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Return vol ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max drawdown&#39;</span><span class="p">]]</span>
-<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Annual Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]</span>
+<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">'Geometric return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Return vol ratio'</span><span class="p">,</span> <span class="s1">'Max drawdown'</span><span class="p">]]</span>
+<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'Annual Return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Sharpe Ratio'</span><span class="p">,</span> <span class="s1">'Max Drawdown'</span><span class="p">]</span>
 
 <span class="c1"># Convert to percentages for better readability</span>
 <span class="n">percentage_metrics</span> <span class="o">=</span> <span class="n">key_metrics</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
-<span class="n">percentage_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">&#39;Annual Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]]</span> <span class="o">*=</span> <span class="mi">100</span>
+<span class="n">percentage_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">'Annual Return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Max Drawdown'</span><span class="p">]]</span> <span class="o">*=</span> <span class="mi">100</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== KEY METRICS COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== KEY METRICS COMPARISON ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">percentage_metrics</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>
 </pre></div>
 </div>
@@ -186,27 +186,27 @@ <h2>Comparative Analysis<a class="headerlink" href="#comparative-analysis" title
 <h2>Ranking Analysis<a class="headerlink" href="#ranking-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Rank assets by different criteria using openseries metrics</span>
 <span class="c1"># Get key metrics for ranking</span>
-<span class="n">returns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">]</span>
-<span class="n">volatilities</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span>
-<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Return vol ratio&#39;</span><span class="p">]</span>
-<span class="n">drawdowns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Max drawdown&#39;</span><span class="p">]</span>
+<span class="n">returns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">]</span>
+<span class="n">volatilities</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span>
+<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Return vol ratio'</span><span class="p">]</span>
+<span class="n">drawdowns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Max drawdown'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ASSET RANKINGS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Ranked by Return (highest first):&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ASSET RANKINGS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Ranked by Return (highest first):"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">returns</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="mi">1</span><span class="p">):</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Ranked by Volatility (lowest first):&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Ranked by Volatility (lowest first):"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">vol</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">volatilities</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="mi">1</span><span class="p">):</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Ranked by Sharpe Ratio (highest first):&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Ranked by Sharpe Ratio (highest first):"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">sharpe</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="mi">1</span><span class="p">):</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Ranked by Max Drawdown (least negative first):&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Ranked by Max Drawdown (least negative first):"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">dd</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">drawdowns</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="mi">1</span><span class="p">):</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -214,7 +214,7 @@ <h2>Ranking Analysis<a class="headerlink" href="#ranking-analysis" title="Link t
 <h2>Correlation Analysis<a class="headerlink" href="#correlation-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Calculate correlation matrix</span>
 <span class="n">correlation_matrix</span> <span class="o">=</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">correl_matrix</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
 
 <span class="c1"># Find most and least correlated pairs</span>
@@ -229,29 +229,29 @@ <h2>Correlation Analysis<a class="headerlink" href="#correlation-analysis" title
 <span class="c1"># Sort by correlation</span>
 <span class="n">corr_pairs</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== HIGHEST CORRELATIONS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== HIGHEST CORRELATIONS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset1</span><span class="p">,</span> <span class="n">asset2</span><span class="p">,</span> <span class="n">corr</span> <span class="ow">in</span> <span class="n">corr_pairs</span><span class="p">[:</span><span class="mi">5</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== LOWEST CORRELATIONS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== LOWEST CORRELATIONS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset1</span><span class="p">,</span> <span class="n">asset2</span><span class="p">,</span> <span class="n">corr</span> <span class="ow">in</span> <span class="n">corr_pairs</span><span class="p">[</span><span class="o">-</span><span class="mi">5</span><span class="p">:]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="risk-return-analysis">
 <h2>Risk-Return Analysis<a class="headerlink" href="#risk-return-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Analyze risk-return using openseries metrics</span>
-<span class="n">returns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">]</span>
-<span class="n">volatilities</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span>
-<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Return vol ratio&#39;</span><span class="p">]</span>
+<span class="n">returns</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">]</span>
+<span class="n">volatilities</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span>
+<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">all_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Return vol ratio'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK-RETURN ANALYSIS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK-RETURN ANALYSIS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset</span> <span class="ow">in</span> <span class="n">returns</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
     <span class="n">ret_pct</span> <span class="o">=</span> <span class="n">returns</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
     <span class="n">vol_pct</span> <span class="o">=</span> <span class="n">volatilities</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
     <span class="n">sharpe</span> <span class="o">=</span> <span class="n">sharpe_ratios</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: Return=</span><span class="si">{</span><span class="n">ret_pct</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%, Volatility=</span><span class="si">{</span><span class="n">vol_pct</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%, Sharpe=</span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: Return=</span><span class="si">{</span><span class="n">ret_pct</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%, Volatility=</span><span class="si">{</span><span class="n">vol_pct</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%, Sharpe=</span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Identify efficient assets (high return per unit risk)</span>
 <span class="c1"># Calculate 75th percentile threshold manually</span>
@@ -259,10 +259,10 @@ <h2>Risk-Return Analysis<a class="headerlink" href="#risk-return-analysis" title
 <span class="n">threshold_idx</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sorted_sharpes</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.25</span><span class="p">)</span>
 <span class="n">efficient_threshold</span> <span class="o">=</span> <span class="n">sorted_sharpes</span><span class="p">[</span><span class="n">threshold_idx</span><span class="p">]</span> <span class="k">if</span> <span class="n">threshold_idx</span> <span class="o">&lt;</span> <span class="nb">len</span><span class="p">(</span><span class="n">sorted_sharpes</span><span class="p">)</span> <span class="k">else</span> <span class="n">sorted_sharpes</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MOST EFFICIENT ASSETS (Sharpe &gt;= </span><span class="si">{</span><span class="n">efficient_threshold</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">) ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MOST EFFICIENT ASSETS (Sharpe &gt;= </span><span class="si">{</span><span class="n">efficient_threshold</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">) ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset</span><span class="p">,</span> <span class="n">sharpe</span> <span class="ow">in</span> <span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
     <span class="k">if</span> <span class="n">sharpe</span> <span class="o">&gt;=</span> <span class="n">efficient_threshold</span><span class="p">:</span>
-        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -270,12 +270,12 @@ <h2>Risk-Return Analysis<a class="headerlink" href="#risk-return-analysis" title
 <h2>Sector/Style Analysis<a class="headerlink" href="#sector-style-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Group assets by characteristics (example grouping)</span>
 <span class="n">asset_groups</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;Mega Cap&#39;</span><span class="p">:</span> <span class="p">[</span><span class="s1">&#39;Apple Inc.&#39;</span><span class="p">,</span> <span class="s1">&#39;Microsoft Corp.&#39;</span><span class="p">,</span> <span class="s1">&#39;Alphabet Inc.&#39;</span><span class="p">,</span> <span class="s1">&#39;Amazon.com Inc.&#39;</span><span class="p">],</span>
-     <span class="s1">&#39;Growth&#39;</span><span class="p">:</span> <span class="p">[</span><span class="s1">&#39;Tesla Inc.&#39;</span><span class="p">,</span> <span class="s1">&#39;NVIDIA Corp.&#39;</span><span class="p">,</span> <span class="s1">&#39;Netflix Inc.&#39;</span><span class="p">],</span>
-     <span class="s1">&#39;Social Media&#39;</span><span class="p">:</span> <span class="p">[</span><span class="s1">&#39;Meta Platforms Inc.&#39;</span><span class="p">]</span>
+     <span class="s1">'Mega Cap'</span><span class="p">:</span> <span class="p">[</span><span class="s1">'Apple Inc.'</span><span class="p">,</span> <span class="s1">'Microsoft Corp.'</span><span class="p">,</span> <span class="s1">'Alphabet Inc.'</span><span class="p">,</span> <span class="s1">'Amazon.com Inc.'</span><span class="p">],</span>
+     <span class="s1">'Growth'</span><span class="p">:</span> <span class="p">[</span><span class="s1">'Tesla Inc.'</span><span class="p">,</span> <span class="s1">'NVIDIA Corp.'</span><span class="p">,</span> <span class="s1">'Netflix Inc.'</span><span class="p">],</span>
+     <span class="s1">'Social Media'</span><span class="p">:</span> <span class="p">[</span><span class="s1">'Meta Platforms Inc.'</span><span class="p">]</span>
 <span class="p">}</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== GROUP ANALYSIS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== GROUP ANALYSIS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">group_name</span><span class="p">,</span> <span class="n">group_assets</span> <span class="ow">in</span> <span class="n">asset_groups</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># Filter assets that exist in our data</span>
      <span class="n">group_series</span> <span class="o">=</span> <span class="p">[</span><span class="n">s</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">label</span> <span class="ow">in</span> <span class="n">group_assets</span><span class="p">]</span>
@@ -284,14 +284,14 @@ <h2>Sector/Style Analysis<a class="headerlink" href="#sector-style-analysis" tit
           <span class="n">group_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">group_series</span><span class="p">)</span>
           <span class="n">group_metrics</span> <span class="o">=</span> <span class="n">group_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 
-          <span class="n">avg_return</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
-          <span class="n">avg_vol</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
-          <span class="n">avg_sharpe</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Return vol ratio&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+          <span class="n">avg_return</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+          <span class="n">avg_vol</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
+          <span class="n">avg_sharpe</span> <span class="o">=</span> <span class="n">group_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Return vol ratio'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
 
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">group_name</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">group_series</span><span class="p">)</span><span class="si">}</span><span class="s2"> assets):&quot;</span><span class="p">)</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Average Return: </span><span class="si">{</span><span class="n">avg_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Average Volatility: </span><span class="si">{</span><span class="n">avg_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Average Sharpe: </span><span class="si">{</span><span class="n">avg_sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">group_name</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">group_series</span><span class="p">)</span><span class="si">}</span><span class="s2"> assets):"</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Average Return: </span><span class="si">{</span><span class="n">avg_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Average Volatility: </span><span class="si">{</span><span class="n">avg_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Average Sharpe: </span><span class="si">{</span><span class="n">avg_sharpe</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -299,45 +299,45 @@ <h2>Sector/Style Analysis<a class="headerlink" href="#sector-style-analysis" tit
 <h2>Time Series Analysis<a class="headerlink" href="#time-series-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Rolling correlation analysis</span>
 <span class="c1"># Pick two assets for detailed analysis</span>
-<span class="n">apple</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">s</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="s2">&quot;Apple&quot;</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="p">)</span>
-<span class="n">microsoft</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">s</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="s2">&quot;Microsoft&quot;</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="p">)</span>
+<span class="n">apple</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">s</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="s2">"Apple"</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="p">)</span>
+<span class="n">microsoft</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">s</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span> <span class="k">if</span> <span class="s2">"Microsoft"</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="p">)</span>
 
 <span class="n">pair_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="p">[</span><span class="n">apple</span><span class="p">,</span> <span class="n">microsoft</span><span class="p">])</span>
 <span class="n">rolling_corr</span> <span class="o">=</span> <span class="n">pair_frame</span><span class="o">.</span><span class="n">rolling_corr</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>  <span class="c1"># 1-year rolling</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ROLLING CORRELATION: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">microsoft</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2"> ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Current correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Correlation range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ROLLING CORRELATION: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2"> vs </span><span class="si">{</span><span class="n">microsoft</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2"> ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Current correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Correlation range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="performance-attribution">
 <h2>Performance Attribution<a class="headerlink" href="#performance-attribution" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Create equal-weighted portfolio for attribution</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Tech Portfolio&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Tech Portfolio"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== PORTFOLIO vs INDIVIDUAL ASSETS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== PORTFOLIO vs INDIVIDUAL ASSETS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Compare with individual assets using OpenFrame</span>
 <span class="n">asset_metrics</span> <span class="o">=</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="n">individual_returns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
-<span class="n">individual_vols</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">individual_returns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">individual_vols</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Diversification benefit:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Diversification benefit:"</span><span class="p">)</span>
 <span class="n">equal_weights</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="o">/</span><span class="n">tech_stocks</span><span class="o">.</span><span class="n">item_count</span><span class="p">]</span> <span class="o">*</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">item_count</span>
 <span class="c1"># Calculate weighted average manually</span>
 <span class="n">weighted_avg_return</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">ret</span> <span class="o">*</span> <span class="n">w</span> <span class="k">for</span> <span class="n">ret</span><span class="p">,</span> <span class="n">w</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">individual_returns</span><span class="p">,</span> <span class="n">equal_weights</span><span class="p">))</span>
 <span class="n">weighted_avg_vol</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">vol</span> <span class="o">*</span> <span class="n">w</span> <span class="k">for</span> <span class="n">vol</span><span class="p">,</span> <span class="n">w</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">individual_vols</span><span class="p">,</span> <span class="n">equal_weights</span><span class="p">))</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weighted avg return: </span><span class="si">{</span><span class="n">weighted_avg_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Portfolio return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weighted avg volatility: </span><span class="si">{</span><span class="n">weighted_avg_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Portfolio volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility reduction: </span><span class="si">{</span><span class="p">(</span><span class="n">weighted_avg_vol</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weighted avg return: </span><span class="si">{</span><span class="n">weighted_avg_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Portfolio return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weighted avg volatility: </span><span class="si">{</span><span class="n">weighted_avg_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Portfolio volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility reduction: </span><span class="si">{</span><span class="p">(</span><span class="n">weighted_avg_vol</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -351,12 +351,12 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
 <span class="n">worst_threshold</span> <span class="o">=</span> <span class="n">market_data</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="mf">0.05</span><span class="p">)</span>
 <span class="n">worst_days</span> <span class="o">=</span> <span class="n">market_data</span><span class="p">[</span><span class="n">market_data</span> <span class="o">&lt;=</span> <span class="n">worst_threshold</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== STRESS TEST ANALYSIS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Market stress threshold: </span><span class="si">{</span><span class="n">worst_threshold</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of stress days: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">worst_days</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== STRESS TEST ANALYSIS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Market stress threshold: </span><span class="si">{</span><span class="n">worst_threshold</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of stress days: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">worst_days</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="c1"># Analyze each asset&#39;s performance during stress</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Asset performance during market stress:&quot;</span><span class="p">)</span>
+<span class="c1"># Analyze each asset's performance during stress</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Asset performance during market stress:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">series</span> <span class="ow">in</span> <span class="n">tech_stocks</span><span class="o">.</span><span class="n">constituents</span><span class="p">:</span>
      <span class="n">series</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>  <span class="c1"># Modifies original</span>
      <span class="n">asset_data</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">tsdf</span>
@@ -364,7 +364,7 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
      <span class="n">stress_returns</span> <span class="o">=</span> <span class="n">asset_data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">worst_days</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>
      <span class="n">avg_stress_return</span> <span class="o">=</span> <span class="n">stress_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">avg_stress_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">avg_stress_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -372,12 +372,12 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
 <h2>Export Multi-Asset Results<a class="headerlink" href="#export-multi-asset-results" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export using openseries native methods</span>
 <span class="c1"># Export frame data</span>
-<span class="n">tech_stocks</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">&#39;multi_asset_analysis.xlsx&#39;</span><span class="p">)</span>
+<span class="n">tech_stocks</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">'multi_asset_analysis.xlsx'</span><span class="p">)</span>
 
 <span class="c1"># Note: For comprehensive Excel export with multiple sheets,</span>
 <span class="c1"># you can use the DataFrame returned by all_properties() and correl_matrix</span>
 <span class="c1"># which are pandas DataFrames and support to_excel() method</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Multi-asset analysis exported to &#39;multi_asset_analysis.xlsx&#39;&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Multi-asset analysis exported to 'multi_asset_analysis.xlsx'"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -385,49 +385,49 @@ <h2>Export Multi-Asset Results<a class="headerlink" href="#export-multi-asset-re
 <h2>Complete Multi-Asset Analysis Workflow<a class="headerlink" href="#complete-multi-asset-analysis-workflow" title="Link to this heading"></a></h2>
 <p>Here’s how to perform a complete multi-asset analysis using openseries methods directly:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Example: Analyze tech stocks using openseries methods</span>
-<span class="n">tech_tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="s2">&quot;GOOGL&quot;</span><span class="p">,</span> <span class="s2">&quot;MSFT&quot;</span><span class="p">,</span> <span class="s2">&quot;AMZN&quot;</span><span class="p">,</span> <span class="s2">&quot;TSLA&quot;</span><span class="p">]</span>
+<span class="n">tech_tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"AAPL"</span><span class="p">,</span> <span class="s2">"GOOGL"</span><span class="p">,</span> <span class="s2">"MSFT"</span><span class="p">,</span> <span class="s2">"AMZN"</span><span class="p">,</span> <span class="s2">"TSLA"</span><span class="p">]</span>
 
 <span class="c1"># Load data using openseries methods</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span> <span class="ow">in</span> <span class="n">tech_tickers</span><span class="p">:</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">ticker</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="ow">not</span> <span class="n">series_list</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;No data loaded&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"No data loaded"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
      <span class="c1"># Create frame using openseries</span>
      <span class="n">frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">series_list</span><span class="p">)</span>
 
      <span class="c1"># Analysis using openseries properties and methods</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;=== MULTI-ASSET ANALYSIS ===&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Assets: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Period: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"=== MULTI-ASSET ANALYSIS ==="</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Assets: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Period: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
      <span class="c1"># Key metrics using openseries all_properties method</span>
      <span class="n">key_metrics</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">(</span>
-          <span class="n">properties</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;geo_ret&#39;</span><span class="p">,</span> <span class="s1">&#39;vol&#39;</span><span class="p">,</span> <span class="s1">&#39;ret_vol_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;max_drawdown&#39;</span><span class="p">]</span>
+          <span class="n">properties</span><span class="o">=</span><span class="p">[</span><span class="s1">'geo_ret'</span><span class="p">,</span> <span class="s1">'vol'</span><span class="p">,</span> <span class="s1">'ret_vol_ratio'</span><span class="p">,</span> <span class="s1">'max_drawdown'</span><span class="p">]</span>
      <span class="p">)</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Key Metrics:&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Key Metrics:"</span><span class="p">)</span>
      <span class="nb">print</span><span class="p">((</span><span class="n">key_metrics</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>  <span class="c1"># Convert to percentages</span>
 
      <span class="c1"># Correlations using openseries correl_matrix property</span>
      <span class="n">correlations</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">correl_matrix</span>
      <span class="n">avg_correlation</span> <span class="o">=</span> <span class="n">correlations</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Average correlation: </span><span class="si">{</span><span class="n">avg_correlation</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Average correlation: </span><span class="si">{</span><span class="n">avg_correlation</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
      <span class="c1"># Create portfolio using openseries make_portfolio method</span>
-     <span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+     <span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
      <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Equal-weight portfolio:&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Equal-weight portfolio:"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
diff --git a/docs/build/html/examples/portfolio_optimization.html b/docs/build/html/examples/portfolio_optimization.html
index e53ab84d..1a66577b 100644
--- a/docs/build/html/examples/portfolio_optimization.html
+++ b/docs/build/html/examples/portfolio_optimization.html
@@ -146,30 +146,30 @@ <h2>Basic Portfolio Optimization Setup<a class="headerlink" href="#basic-portfol
 
 <span class="c1"># Define investment universe</span>
 <span class="n">universe</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;VTI&quot;</span><span class="p">:</span> <span class="s2">&quot;Total Stock Market&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VEA&quot;</span><span class="p">:</span> <span class="s2">&quot;Developed Markets&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VWO&quot;</span><span class="p">:</span> <span class="s2">&quot;Emerging Markets&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;BND&quot;</span><span class="p">:</span> <span class="s2">&quot;Total Bond Market&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VNQ&quot;</span><span class="p">:</span> <span class="s2">&quot;Real Estate&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VDE&quot;</span><span class="p">:</span> <span class="s2">&quot;Energy&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VGT&quot;</span><span class="p">:</span> <span class="s2">&quot;Technology&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VHT&quot;</span><span class="p">:</span> <span class="s2">&quot;Healthcare&quot;</span>
+     <span class="s2">"VTI"</span><span class="p">:</span> <span class="s2">"Total Stock Market"</span><span class="p">,</span>
+     <span class="s2">"VEA"</span><span class="p">:</span> <span class="s2">"Developed Markets"</span><span class="p">,</span>
+     <span class="s2">"VWO"</span><span class="p">:</span> <span class="s2">"Emerging Markets"</span><span class="p">,</span>
+     <span class="s2">"BND"</span><span class="p">:</span> <span class="s2">"Total Bond Market"</span><span class="p">,</span>
+     <span class="s2">"VNQ"</span><span class="p">:</span> <span class="s2">"Real Estate"</span><span class="p">,</span>
+     <span class="s2">"VDE"</span><span class="p">:</span> <span class="s2">"Energy"</span><span class="p">,</span>
+     <span class="s2">"VGT"</span><span class="p">:</span> <span class="s2">"Technology"</span><span class="p">,</span>
+     <span class="s2">"VHT"</span><span class="p">:</span> <span class="s2">"Healthcare"</span>
 <span class="p">}</span>
 
 <span class="c1"># Load data</span>
 <span class="n">assets</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">universe</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">assets</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Create investment universe frame</span>
 <span class="n">investment_universe</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">assets</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Investment universe: </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Period: </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Investment universe: </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Period: </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -183,44 +183,44 @@ <h2>Mean-Variance Optimization<a class="headerlink" href="#mean-variance-optimiz
      <span class="n">seed</span><span class="o">=</span><span class="mi">42</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== EFFICIENT FRONTIER RESULTS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Generated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frontier_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> efficient portfolios&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulated_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== EFFICIENT FRONTIER RESULTS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Generated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frontier_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> efficient portfolios"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulated_df</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios"</span><span class="p">)</span>
 
 <span class="c1"># Find key portfolios</span>
-<span class="n">returns</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span>
-<span class="n">volatilities</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span>
+<span class="n">returns</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span>
+<span class="n">volatilities</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span>
 <span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">returns</span> <span class="o">/</span> <span class="n">volatilities</span>
 
 <span class="c1"># Maximum Sharpe ratio portfolio</span>
 <span class="n">max_sharpe_idx</span> <span class="o">=</span> <span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">idxmax</span><span class="p">()</span>
 <span class="n">max_sharpe_weights</span> <span class="o">=</span> <span class="n">optimal_portfolio</span><span class="p">[</span><span class="o">-</span><span class="nb">len</span><span class="p">(</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">constituents</span><span class="p">):]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MAXIMUM SHARPE RATIO PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Expected Return: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MAXIMUM SHARPE RATIO PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Expected Return: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">'ret'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">'stdev'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Optimal Weights:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Optimal Weights:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">max_sharpe_weights</span><span class="p">):</span>
      <span class="n">asset_name</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">constituents</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">label</span>
      <span class="k">if</span> <span class="n">weight</span> <span class="o">&gt;</span> <span class="mf">0.01</span><span class="p">:</span>  <span class="c1"># Only show weights &gt; 1%</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Minimum volatility portfolio</span>
 <span class="n">min_vol_idx</span> <span class="o">=</span> <span class="n">volatilities</span><span class="o">.</span><span class="n">idxmin</span><span class="p">()</span>
 <span class="n">min_vol_weights</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">min_vol_idx</span><span class="p">][</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MINIMUM VOLATILITY PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Expected Return: </span><span class="si">{</span><span class="n">min_vol_row</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">min_vol_row</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">min_vol_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MINIMUM VOLATILITY PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Expected Return: </span><span class="si">{</span><span class="n">min_vol_row</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">min_vol_row</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">min_vol_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Minimum Volatility Weights:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Minimum Volatility Weights:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">:</span>
      <span class="n">weight</span> <span class="o">=</span> <span class="n">min_vol_row</span><span class="p">[</span><span class="n">col</span><span class="p">]</span>
      <span class="k">if</span> <span class="n">weight</span> <span class="o">&gt;</span> <span class="mf">0.01</span><span class="p">:</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">col</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">col</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -234,36 +234,36 @@ <h2>Monte Carlo Portfolio Simulation<a class="headerlink" href="#monte-carlo-por
      <span class="n">seed</span><span class="o">=</span><span class="mi">42</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MONTE CARLO SIMULATION ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulation_results</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MONTE CARLO SIMULATION ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulation_results</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios"</span><span class="p">)</span>
 
-<span class="n">sim_returns</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
-<span class="n">sim_volatilities</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">sim_returns</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">sim_volatilities</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
 <span class="n">sim_sharpe_ratios</span> <span class="o">=</span> <span class="n">sim_returns</span> <span class="o">/</span> <span class="n">sim_volatilities</span>
 
 <span class="c1"># Statistics of simulated portfolios</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Simulation Statistics:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return range: </span><span class="si">{</span><span class="n">sim_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_returns</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility range: </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe range: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Simulation Statistics:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return range: </span><span class="si">{</span><span class="n">sim_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_returns</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility range: </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe range: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Best portfolios from simulation</span>
 <span class="n">sorted_indices</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sim_sharpe_ratios</span><span class="p">)),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">i</span><span class="p">:</span> <span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">top_sharpe_indices</span> <span class="o">=</span> <span class="n">sorted_indices</span><span class="p">[:</span><span class="mi">5</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== TOP 5 SIMULATED PORTFOLIOS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== TOP 5 SIMULATED PORTFOLIOS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="n">top_sharpe_indices</span><span class="p">)):</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Rank </span><span class="si">{</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">sim_returns</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Rank </span><span class="si">{</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">sim_returns</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">sim_volatilities</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
      <span class="n">weights</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="n">investment_universe</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  Weights:&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  Weights:"</span><span class="p">)</span>
      <span class="k">for</span> <span class="n">j</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">weights</span><span class="p">):</span>
           <span class="k">if</span> <span class="n">weight</span> <span class="o">&gt;</span> <span class="mf">0.05</span><span class="p">:</span>  <span class="c1"># Only show weights &gt; 5%</span>
                 <span class="n">asset_name</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">constituents</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">label</span>
-                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;    </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"    </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -273,15 +273,15 @@ <h2>Risk-Based Portfolio Strategies<a class="headerlink" href="#risk-based-portf
 <h3>Equal Weight Portfolio<a class="headerlink" href="#equal-weight-portfolio" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Equal weight portfolio using native weight_strat</span>
 <span class="n">equal_weight_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span>
 <span class="p">)</span>
 <span class="n">equal_weight_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">equal_weight_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== EQUAL WEIGHT PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== EQUAL WEIGHT PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -289,15 +289,15 @@ <h3>Equal Weight Portfolio<a class="headerlink" href="#equal-weight-portfolio" t
 <h3>Inverse Volatility Portfolio<a class="headerlink" href="#inverse-volatility-portfolio" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Inverse volatility weighting using native weight_strat</span>
 <span class="n">inv_vol_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Inverse Volatility&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;inv_vol&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Inverse Volatility"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"inv_vol"</span>
 <span class="p">)</span>
 <span class="n">inv_vol_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">inv_vol_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== INVERSE VOLATILITY PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== INVERSE VOLATILITY PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe: </span><span class="si">{</span><span class="n">inv_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -307,15 +307,15 @@ <h3>Maximum Diversification Portfolio<a class="headerlink" href="#maximum-divers
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Maximum diversification portfolio using native weight_strat</span>
 <span class="c1"># This may fail with MaxDiversificationNaNError or MaxDiversificationNegativeWeightsError</span>
 <span class="n">max_div_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Maximum Diversification&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;max_div&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Maximum Diversification"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"max_div"</span>
 <span class="p">)</span>
 <span class="n">max_div_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">max_div_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MAXIMUM DIVERSIFICATION PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MAXIMUM DIVERSIFICATION PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -324,15 +324,15 @@ <h3>Maximum Diversification Portfolio<a class="headerlink" href="#maximum-divers
 <h2>Minimum Volatility Overweight Portfolio<a class="headerlink" href="#minimum-volatility-overweight-portfolio" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Minimum volatility overweight portfolio using native weight_strat</span>
 <span class="n">min_vol_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Min Vol Overweight&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;min_vol_overweight&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Min Vol Overweight"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"min_vol_overweight"</span>
 <span class="p">)</span>
 <span class="n">min_vol_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">min_vol_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MINIMUM VOLATILITY OVERWEIGHT PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MINIMUM VOLATILITY OVERWEIGHT PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -347,18 +347,18 @@ <h2>Portfolio Comparison<a class="headerlink" href="#portfolio-comparison" title
 <span class="p">]</span>
 
 <span class="c1"># Add optimized portfolios if available</span>
-<span class="k">if</span> <span class="s1">&#39;max_sharpe_weights&#39;</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
+<span class="k">if</span> <span class="s1">'max_sharpe_weights'</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
      <span class="n">investment_universe</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="n">max_sharpe_weights</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
      <span class="n">max_sharpe_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-          <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Max Sharpe (Optimized)&quot;</span>
+          <span class="n">name</span><span class="o">=</span><span class="s2">"Max Sharpe (Optimized)"</span>
      <span class="p">)</span>
      <span class="n">max_sharpe_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">max_sharpe_portfolio_df</span><span class="p">)</span>
      <span class="n">portfolios</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">max_sharpe_portfolio</span><span class="p">)</span>
 
-<span class="k">if</span> <span class="s1">&#39;min_vol_weights&#39;</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
+<span class="k">if</span> <span class="s1">'min_vol_weights'</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
      <span class="n">investment_universe</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="n">min_vol_weights</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
      <span class="n">min_vol_portfolio_df</span> <span class="o">=</span> <span class="n">investment_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-          <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Min Vol (Optimized)&quot;</span>
+          <span class="n">name</span><span class="o">=</span><span class="s2">"Min Vol (Optimized)"</span>
      <span class="p">)</span>
      <span class="n">min_vol_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">min_vol_portfolio_df</span><span class="p">)</span>
      <span class="n">portfolios</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">min_vol_portfolio</span><span class="p">)</span>
@@ -368,10 +368,10 @@ <h2>Portfolio Comparison<a class="headerlink" href="#portfolio-comparison" title
 <span class="n">comparison_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 
 <span class="c1"># Display key metrics</span>
-<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">&#39;geo_ret&#39;</span><span class="p">,</span> <span class="s1">&#39;vol&#39;</span><span class="p">,</span> <span class="s1">&#39;ret_vol_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;max_drawdown&#39;</span><span class="p">]]</span>
-<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Annual Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]</span>
+<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">'geo_ret'</span><span class="p">,</span> <span class="s1">'vol'</span><span class="p">,</span> <span class="s1">'ret_vol_ratio'</span><span class="p">,</span> <span class="s1">'max_drawdown'</span><span class="p">]]</span>
+<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'Annual Return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Sharpe Ratio'</span><span class="p">,</span> <span class="s1">'Max Drawdown'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== PORTFOLIO STRATEGY COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== PORTFOLIO STRATEGY COMPARISON ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">((</span><span class="n">key_metrics</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>  <span class="c1"># Convert to percentages</span>
 </pre></div>
 </div>
@@ -412,7 +412,7 @@ <h3>Weight Strategy Details<a class="headerlink" href="#weight-strategy-details"
 <span class="p">)</span>
 
 <span class="c1"># This may fail with MaxDiversificationNaNError or MaxDiversificationNegativeWeightsError</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Max Div&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;max_div&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Max Div"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"max_div"</span><span class="p">)</span>
 </pre></div>
 </div>
 </dd>
@@ -423,10 +423,10 @@ <h3>Weight Strategy Details<a class="headerlink" href="#weight-strategy-details"
 <h2>Backtesting Framework<a class="headerlink" href="#backtesting-framework" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Define strategies to backtest using native weight_strat</span>
 <span class="n">strategies</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;Equal Weight&#39;</span><span class="p">:</span> <span class="s1">&#39;eq_weights&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Inverse Volatility&#39;</span><span class="p">:</span> <span class="s1">&#39;inv_vol&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Max Diversification&#39;</span><span class="p">:</span> <span class="s1">&#39;max_div&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Min Vol Overweight&#39;</span><span class="p">:</span> <span class="s1">&#39;min_vol_overweight&#39;</span>
+     <span class="s1">'Equal Weight'</span><span class="p">:</span> <span class="s1">'eq_weights'</span><span class="p">,</span>
+     <span class="s1">'Inverse Volatility'</span><span class="p">:</span> <span class="s1">'inv_vol'</span><span class="p">,</span>
+     <span class="s1">'Max Diversification'</span><span class="p">:</span> <span class="s1">'max_div'</span><span class="p">,</span>
+     <span class="s1">'Min Vol Overweight'</span><span class="p">:</span> <span class="s1">'min_vol_overweight'</span>
 <span class="p">}</span>
 
 <span class="c1"># Run backtest using native strategies</span>
@@ -439,28 +439,28 @@ <h2>Backtesting Framework<a class="headerlink" href="#backtesting-framework" tit
      <span class="p">)</span>
      <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
      <span class="n">backtest_results</span><span class="p">[</span><span class="n">strategy_name</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
-          <span class="s1">&#39;return&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
-          <span class="s1">&#39;volatility&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
-          <span class="s1">&#39;sharpe&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
-          <span class="s1">&#39;max_drawdown&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">,</span>
-          <span class="s1">&#39;calmar&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span> <span class="o">/</span> <span class="nb">abs</span><span class="p">(</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">)</span> <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span> <span class="o">!=</span> <span class="mi">0</span> <span class="k">else</span> <span class="nb">float</span><span class="p">(</span><span class="s1">&#39;nan&#39;</span><span class="p">)</span>
+          <span class="s1">'return'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
+          <span class="s1">'volatility'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
+          <span class="s1">'sharpe'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
+          <span class="s1">'max_drawdown'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">,</span>
+          <span class="s1">'calmar'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span> <span class="o">/</span> <span class="nb">abs</span><span class="p">(</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">)</span> <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span> <span class="o">!=</span> <span class="mi">0</span> <span class="k">else</span> <span class="nb">float</span><span class="p">(</span><span class="s1">'nan'</span><span class="p">)</span>
      <span class="p">}</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== BACKTEST RESULTS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== BACKTEST RESULTS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">strategy_name</span><span class="p">,</span> <span class="n">metrics</span> <span class="ow">in</span> <span class="n">backtest_results</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">strategy_name</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;return&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;volatility&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;max_drawdown&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Calmar: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;calmar&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">strategy_name</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'return'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'volatility'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'max_drawdown'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Calmar: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'calmar'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rank strategies</span>
-<span class="n">sorted_strategies</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">backtest_results</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;sharpe&#39;</span><span class="p">],</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">sorted_strategies</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">backtest_results</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="s1">'sharpe'</span><span class="p">],</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">best_strategy</span> <span class="o">=</span> <span class="n">sorted_strategies</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Best performing strategy: </span><span class="si">{</span><span class="n">best_strategy</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe ratio: </span><span class="si">{</span><span class="n">sorted_strategies</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">][</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Best performing strategy: </span><span class="si">{</span><span class="n">best_strategy</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe ratio: </span><span class="si">{</span><span class="n">sorted_strategies</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">][</span><span class="s1">'sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -468,12 +468,12 @@ <h2>Backtesting Framework<a class="headerlink" href="#backtesting-framework" tit
 <h2>Export Optimization Results<a class="headerlink" href="#export-optimization-results" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export using openseries native methods</span>
 <span class="c1"># Export frame data</span>
-<span class="n">investment_universe</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">&#39;portfolio_optimization_results.xlsx&#39;</span><span class="p">)</span>
+<span class="n">investment_universe</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">'portfolio_optimization_results.xlsx'</span><span class="p">)</span>
 
 <span class="c1"># Note: For comprehensive Excel export with multiple sheets,</span>
 <span class="c1"># the DataFrames returned by all_properties() and correl_matrix</span>
 <span class="c1"># are pandas DataFrames and support to_excel() method</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Optimization results exported to &#39;portfolio_optimization_results.xlsx&#39;&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Optimization results exported to 'portfolio_optimization_results.xlsx'"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -492,28 +492,28 @@ <h3>Using Real Fund Data for Optimization<a class="headerlink" href="#using-real
 
 <span class="c1"># Define fund universe for optimization</span>
 <span class="n">fund_universe_isins</span> <span class="o">=</span> <span class="p">[</span>
-     <span class="s2">&quot;SE0015243886&quot;</span><span class="p">,</span>  <span class="c1"># Global High Yield</span>
-     <span class="s2">&quot;SE0011337195&quot;</span><span class="p">,</span>  <span class="c1"># Global Equity</span>
-     <span class="s2">&quot;SE0011670843&quot;</span><span class="p">,</span>  <span class="c1"># Global Bond</span>
-     <span class="s2">&quot;SE0017832280&quot;</span><span class="p">,</span>  <span class="c1"># Alternative Strategy</span>
-     <span class="s2">&quot;SE0017832330&quot;</span><span class="p">,</span>  <span class="c1"># Multi-Asset Strategy</span>
+     <span class="s2">"SE0015243886"</span><span class="p">,</span>  <span class="c1"># Global High Yield</span>
+     <span class="s2">"SE0011337195"</span><span class="p">,</span>  <span class="c1"># Global Equity</span>
+     <span class="s2">"SE0011670843"</span><span class="p">,</span>  <span class="c1"># Global Bond</span>
+     <span class="s2">"SE0017832280"</span><span class="p">,</span>  <span class="c1"># Alternative Strategy</span>
+     <span class="s2">"SE0017832330"</span><span class="p">,</span>  <span class="c1"># Multi-Asset Strategy</span>
 <span class="p">]</span>
 
 <span class="c1"># Load fund data using openseries methods</span>
-<span class="n">response</span> <span class="o">=</span> <span class="n">requests_get</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">&quot;https://api.captor.se/public/api/nav&quot;</span><span class="p">,</span> <span class="n">timeout</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
+<span class="n">response</span> <span class="o">=</span> <span class="n">requests_get</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://api.captor.se/public/api/nav"</span><span class="p">,</span> <span class="n">timeout</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
 <span class="n">response</span><span class="o">.</span><span class="n">raise_for_status</span><span class="p">()</span>
 
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="n">result</span> <span class="o">=</span> <span class="n">response</span><span class="o">.</span><span class="n">json</span><span class="p">()</span>
 
 <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">result</span><span class="p">:</span>
-     <span class="k">if</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;isin&quot;</span><span class="p">]</span> <span class="ow">in</span> <span class="n">fund_universe_isins</span><span class="p">:</span>
+     <span class="k">if</span> <span class="n">data</span><span class="p">[</span><span class="s2">"isin"</span><span class="p">]</span> <span class="ow">in</span> <span class="n">fund_universe_isins</span><span class="p">:</span>
           <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-                <span class="n">name</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;longName&quot;</span><span class="p">],</span>
-                <span class="n">isin</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;isin&quot;</span><span class="p">],</span>
-                <span class="n">baseccy</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;currency&quot;</span><span class="p">],</span>
-                <span class="n">dates</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;dates&quot;</span><span class="p">],</span>
-                <span class="n">values</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;navPerUnit&quot;</span><span class="p">],</span>
+                <span class="n">name</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">"longName"</span><span class="p">],</span>
+                <span class="n">isin</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">"isin"</span><span class="p">],</span>
+                <span class="n">baseccy</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">"currency"</span><span class="p">],</span>
+                <span class="n">dates</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">"dates"</span><span class="p">],</span>
+                <span class="n">values</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">"navPerUnit"</span><span class="p">],</span>
                 <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">,</span>
           <span class="p">)</span>
           <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
@@ -524,8 +524,8 @@ <h3>Using Real Fund Data for Optimization<a class="headerlink" href="#using-real
 <span class="c1"># Process data using openseries methods</span>
 <span class="n">fund_universe</span> <span class="o">=</span> <span class="n">fund_universe</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">()</span><span class="o">.</span><span class="n">trunc_frame</span><span class="p">()</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Fund universe created with </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> funds&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Analysis period: </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Fund universe created with </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> funds"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Analysis period: </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -538,8 +538,8 @@ <h3>Advanced Optimization with Real Data<a class="headerlink" href="#advanced-op
 
 <span class="c1"># Create current portfolio (equal weights)</span>
 <span class="n">current_portfolio_df</span> <span class="o">=</span> <span class="n">fund_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Current Portfolio&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">,</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Current Portfolio"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">,</span>
 <span class="p">)</span>
 <span class="n">current_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">current_portfolio_df</span><span class="p">)</span>
 
@@ -566,16 +566,16 @@ <h3>Advanced Optimization with Real Data<a class="headerlink" href="#advanced-op
      <span class="n">sim_frame</span><span class="o">=</span><span class="n">simulated_portfolios</span><span class="p">,</span>
      <span class="n">line_frame</span><span class="o">=</span><span class="n">frontier</span><span class="p">,</span>
      <span class="n">point_frame</span><span class="o">=</span><span class="n">plot_data</span><span class="p">,</span>
-     <span class="n">point_frame_mode</span><span class="o">=</span><span class="s2">&quot;markers+text&quot;</span><span class="p">,</span>
-     <span class="n">title</span><span class="o">=</span><span class="s2">&quot;Real Fund Portfolio Optimization&quot;</span><span class="p">,</span>
+     <span class="n">point_frame_mode</span><span class="o">=</span><span class="s2">"markers+text"</span><span class="p">,</span>
+     <span class="n">title</span><span class="o">=</span><span class="s2">"Real Fund Portfolio Optimization"</span><span class="p">,</span>
      <span class="n">add_logo</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
      <span class="n">auto_open</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
-     <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;div&quot;</span><span class="p">,</span>
+     <span class="n">output_type</span><span class="o">=</span><span class="s2">"div"</span><span class="p">,</span>
 <span class="p">)</span>
 <span class="n">optimization_plot</span> <span class="o">=</span> <span class="n">optimization_plot</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">width</span><span class="o">=</span><span class="mi">1200</span><span class="p">,</span> <span class="n">height</span><span class="o">=</span><span class="mi">700</span><span class="p">)</span>
 
 <span class="c1"># Display the optimization results</span>
-<span class="n">optimization_plot</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="n">config</span><span class="o">=</span><span class="n">figdict</span><span class="p">[</span><span class="s2">&quot;config&quot;</span><span class="p">])</span>
+<span class="n">optimization_plot</span><span class="o">.</span><span class="n">show</span><span class="p">(</span><span class="n">config</span><span class="o">=</span><span class="n">figdict</span><span class="p">[</span><span class="s2">"config"</span><span class="p">])</span>
 </pre></div>
 </div>
 </section>
@@ -586,38 +586,38 @@ <h3>Performance Comparison Analysis<a class="headerlink" href="#performance-comp
 
 <span class="c1"># Equal weight portfolio</span>
 <span class="n">equal_weight_portfolio_df</span> <span class="o">=</span> <span class="n">fund_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span>
 <span class="p">)</span>
 <span class="n">equal_weight_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">equal_weight_portfolio_df</span><span class="p">)</span>
-<span class="n">strategies</span><span class="p">[</span><span class="s1">&#39;Equal Weight&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">equal_weight_portfolio</span>
+<span class="n">strategies</span><span class="p">[</span><span class="s1">'Equal Weight'</span><span class="p">]</span> <span class="o">=</span> <span class="n">equal_weight_portfolio</span>
 
 <span class="c1"># Optimal portfolio from efficient frontier</span>
 <span class="n">fund_universe</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="n">optimal_portfolio</span><span class="p">[</span><span class="o">-</span><span class="n">fund_universe</span><span class="o">.</span><span class="n">item_count</span><span class="p">:]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
-<span class="n">optimal_portfolio_df</span> <span class="o">=</span> <span class="n">fund_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Optimal Portfolio&quot;</span><span class="p">)</span>
+<span class="n">optimal_portfolio_df</span> <span class="o">=</span> <span class="n">fund_universe</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Optimal Portfolio"</span><span class="p">)</span>
 <span class="n">optimal_portfolio_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">optimal_portfolio_df</span><span class="p">)</span>
-<span class="n">strategies</span><span class="p">[</span><span class="s1">&#39;Optimal Portfolio&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">optimal_portfolio_series</span>
+<span class="n">strategies</span><span class="p">[</span><span class="s1">'Optimal Portfolio'</span><span class="p">]</span> <span class="o">=</span> <span class="n">optimal_portfolio_series</span>
 
 <span class="c1"># Create comparison frame</span>
 <span class="n">comparison_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="nb">list</span><span class="p">(</span><span class="n">strategies</span><span class="o">.</span><span class="n">values</span><span class="p">()))</span>
 <span class="n">comparison_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 
 <span class="c1"># Display key metrics</span>
-<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">&#39;geo_ret&#39;</span><span class="p">,</span> <span class="s1">&#39;vol&#39;</span><span class="p">,</span> <span class="s1">&#39;ret_vol_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;max_drawdown&#39;</span><span class="p">]]</span>
-<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Annual Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]</span>
+<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">'geo_ret'</span><span class="p">,</span> <span class="s1">'vol'</span><span class="p">,</span> <span class="s1">'ret_vol_ratio'</span><span class="p">,</span> <span class="s1">'max_drawdown'</span><span class="p">]]</span>
+<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'Annual Return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Sharpe Ratio'</span><span class="p">,</span> <span class="s1">'Max Drawdown'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== PORTFOLIO STRATEGY COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== PORTFOLIO STRATEGY COMPARISON ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">((</span><span class="n">key_metrics</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>
 
 <span class="c1"># Calculate improvement metrics</span>
 <span class="n">improvement</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;Return Improvement&#39;</span><span class="p">:</span> <span class="p">(</span><span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">geo_ret</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span>
-     <span class="s1">&#39;Volatility Change&#39;</span><span class="p">:</span> <span class="p">(</span><span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">vol</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span>
-     <span class="s1">&#39;Sharpe Improvement&#39;</span><span class="p">:</span> <span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">ret_vol_ratio</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
+     <span class="s1">'Return Improvement'</span><span class="p">:</span> <span class="p">(</span><span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">geo_ret</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span>
+     <span class="s1">'Volatility Change'</span><span class="p">:</span> <span class="p">(</span><span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">vol</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span><span class="p">,</span>
+     <span class="s1">'Sharpe Improvement'</span><span class="p">:</span> <span class="n">optimal_portfolio_series</span><span class="o">.</span><span class="n">ret_vol_ratio</span> <span class="o">-</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
 <span class="p">}</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== OPTIMIZATION IMPROVEMENTS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== OPTIMIZATION IMPROVEMENTS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">metric</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">improvement</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">metric</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">value</span><span class="si">:</span><span class="s2">+.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">metric</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">value</span><span class="si">:</span><span class="s2">+.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -626,28 +626,28 @@ <h3>Performance Comparison Analysis<a class="headerlink" href="#performance-comp
 <h2>Complete Optimization Workflow<a class="headerlink" href="#complete-optimization-workflow" title="Link to this heading"></a></h2>
 <p>Here’s how to perform portfolio optimization using openseries methods directly:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Example: Optimize ETF portfolio using openseries methods</span>
-<span class="n">etf_tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;VTI&quot;</span><span class="p">,</span> <span class="s2">&quot;VEA&quot;</span><span class="p">,</span> <span class="s2">&quot;VWO&quot;</span><span class="p">,</span> <span class="s2">&quot;BND&quot;</span><span class="p">,</span> <span class="s2">&quot;VNQ&quot;</span><span class="p">]</span>
+<span class="n">etf_tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"VTI"</span><span class="p">,</span> <span class="s2">"VEA"</span><span class="p">,</span> <span class="s2">"VWO"</span><span class="p">,</span> <span class="s2">"BND"</span><span class="p">,</span> <span class="s2">"VNQ"</span><span class="p">]</span>
 
 <span class="c1"># Load data using openseries methods</span>
 <span class="n">assets</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span> <span class="ow">in</span> <span class="n">etf_tickers</span><span class="p">:</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">ticker</span><span class="p">)</span>
      <span class="n">assets</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">assets</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mi">2</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Need at least 2 assets for optimization&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"Need at least 2 assets for optimization"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
      <span class="n">frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">assets</span><span class="p">)</span>
 
      <span class="c1"># Use openseries native weight strategies</span>
      <span class="n">strategies</span> <span class="o">=</span> <span class="p">{</span>
-          <span class="s1">&#39;Equal Weight&#39;</span><span class="p">:</span> <span class="s1">&#39;eq_weights&#39;</span><span class="p">,</span>
-          <span class="s1">&#39;Inverse Volatility&#39;</span><span class="p">:</span> <span class="s1">&#39;inv_vol&#39;</span><span class="p">,</span>
-          <span class="s1">&#39;Max Diversification&#39;</span><span class="p">:</span> <span class="s1">&#39;max_div&#39;</span><span class="p">,</span>
-          <span class="s1">&#39;Min Vol Overweight&#39;</span><span class="p">:</span> <span class="s1">&#39;min_vol_overweight&#39;</span>
+          <span class="s1">'Equal Weight'</span><span class="p">:</span> <span class="s1">'eq_weights'</span><span class="p">,</span>
+          <span class="s1">'Inverse Volatility'</span><span class="p">:</span> <span class="s1">'inv_vol'</span><span class="p">,</span>
+          <span class="s1">'Max Diversification'</span><span class="p">:</span> <span class="s1">'max_div'</span><span class="p">,</span>
+          <span class="s1">'Min Vol Overweight'</span><span class="p">:</span> <span class="s1">'min_vol_overweight'</span>
      <span class="p">}</span>
 
      <span class="c1"># Create portfolios using openseries make_portfolio method</span>
@@ -657,19 +657,19 @@ <h2>Complete Optimization Workflow<a class="headerlink" href="#complete-optimiza
           <span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="n">weight_strat</span><span class="p">)</span>
           <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
           <span class="n">results</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
-                <span class="s1">&#39;Return&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
-                <span class="s1">&#39;Volatility&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
-                <span class="s1">&#39;Sharpe&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
-                <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span>
+                <span class="s1">'Return'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
+                <span class="s1">'Volatility'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
+                <span class="s1">'Sharpe'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
+                <span class="s1">'Max Drawdown'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span>
           <span class="p">}</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== PORTFOLIO OPTIMIZATION RESULTS ===&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"=== PORTFOLIO OPTIMIZATION RESULTS ==="</span><span class="p">)</span>
      <span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">metrics</span> <span class="ow">in</span> <span class="n">results</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;Return&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;Sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'Return'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'Sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'Max Drawdown'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
diff --git a/docs/build/html/examples/single_asset.html b/docs/build/html/examples/single_asset.html
index 25a0ad5d..84345bd1 100644
--- a/docs/build/html/examples/single_asset.html
+++ b/docs/build/html/examples/single_asset.html
@@ -131,34 +131,34 @@ <h2>Basic Setup<a class="headerlink" href="#basic-setup" title="Link to this hea
 <span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 
 <span class="c1"># Download Apple stock data</span>
-<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;AAPL&quot;</span><span class="p">)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"AAPL"</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenTimeSeries</span>
 <span class="n">apple</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
 <span class="p">)</span>
 
 <span class="c1"># Set descriptive label</span>
-<span class="n">apple</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Apple Inc. (AAPL)&quot;</span><span class="p">)</span>
+<span class="n">apple</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Apple Inc. (AAPL)"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Date range: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="performance-analysis">
 <h2>Performance Analysis<a class="headerlink" href="#performance-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Basic performance metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== PERFORMANCE METRICS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== PERFORMANCE METRICS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Get all metrics at once</span>
 <span class="n">all_metrics</span> <span class="o">=</span> <span class="n">apple</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ALL METRICS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ALL METRICS ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">all_metrics</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -166,13 +166,13 @@ <h2>Performance Analysis<a class="headerlink" href="#performance-analysis" title
 <section id="risk-analysis">
 <h2>Risk Analysis<a class="headerlink" href="#risk-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Risk metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== RISK ANALYSIS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Drawdown Date: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">max_drawdown_date</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR (daily): </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR (daily): </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Single Day: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">worst</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== RISK ANALYSIS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Drawdown Date: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">max_drawdown_date</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR (daily): </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR (daily): </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Single Day: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">worst</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -180,7 +180,7 @@ <h2>Risk Analysis<a class="headerlink" href="#risk-analysis" title="Link to this
 <h2>Time Series Transformations<a class="headerlink" href="#time-series-transformations" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Convert to returns (modifies original)</span>
 <span class="n">apple</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Returns series length: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Returns series length: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Create drawdown series (modifies original)</span>
 <span class="n">apple</span><span class="o">.</span><span class="n">to_drawdown_series</span><span class="p">()</span>
@@ -189,8 +189,8 @@ <h2>Time Series Transformations<a class="headerlink" href="#time-series-transfor
 <span class="n">apple</span><span class="o">.</span><span class="n">value_to_log</span><span class="p">()</span>
 
 <span class="c1"># Resample to monthly (modifies original)</span>
-<span class="n">apple</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monthly data points: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="n">apple</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monthly data points: </span><span class="si">{</span><span class="n">apple</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -198,8 +198,8 @@ <h2>Time Series Transformations<a class="headerlink" href="#time-series-transfor
 <h2>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Rolling volatility (1-year window)</span>
 <span class="n">rolling_vol</span> <span class="o">=</span> <span class="n">apple</span><span class="o">.</span><span class="n">rolling_vol</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Current 1Y volatility: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average 1Y volatility: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Current 1Y volatility: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average 1Y volatility: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rolling returns (30-day)</span>
 <span class="n">rolling_returns</span> <span class="o">=</span> <span class="n">apple</span><span class="o">.</span><span class="n">rolling_return</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">30</span><span class="p">)</span>
@@ -227,24 +227,24 @@ <h2>Calendar Analysis<a class="headerlink" href="#calendar-analysis" title="Link
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Annual returns by calendar year</span>
 <span class="n">years</span> <span class="o">=</span> <span class="p">[</span><span class="mi">2019</span><span class="p">,</span> <span class="mi">2020</span><span class="p">,</span> <span class="mi">2021</span><span class="p">,</span> <span class="mi">2022</span><span class="p">,</span> <span class="mi">2023</span><span class="p">,</span> <span class="mi">2024</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== CALENDAR YEAR RETURNS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== CALENDAR YEAR RETURNS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">year</span> <span class="ow">in</span> <span class="n">years</span><span class="p">:</span>
      <span class="c1"># This may fail if no data exists for the year</span>
      <span class="n">year_return</span> <span class="o">=</span> <span class="n">apple</span><span class="o">.</span><span class="n">value_ret_calendar_period</span><span class="p">(</span><span class="n">year</span><span class="o">=</span><span class="n">year</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">year</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">year_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">year</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">year_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="export-results">
 <h2>Export Results<a class="headerlink" href="#export-results" title="Link to this heading"></a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export to Excel</span>
-<span class="n">apple</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s2">&quot;apple_analysis.xlsx&quot;</span><span class="p">)</span>
+<span class="n">apple</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s2">"apple_analysis.xlsx"</span><span class="p">)</span>
 
 <span class="c1"># Export metrics to CSV</span>
-<span class="n">all_metrics</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;apple_metrics.csv&quot;</span><span class="p">)</span>
+<span class="n">all_metrics</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">"apple_metrics.csv"</span><span class="p">)</span>
 
 <span class="c1"># Export to JSON</span>
-<span class="n">apple</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="s2">&quot;apple_data.json&quot;</span><span class="p">)</span>
+<span class="n">apple</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="s2">"apple_data.json"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -255,55 +255,55 @@ <h2>Complete Analysis Workflow<a class="headerlink" href="#complete-analysis-wor
 <span class="kn">from</span><span class="w"> </span><span class="nn">openseries</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenTimeSeries</span>
 
 <span class="c1"># Example: Analyze Apple stock using openseries methods</span>
-<span class="n">ticker_symbol</span> <span class="o">=</span> <span class="s2">&quot;AAPL&quot;</span>
+<span class="n">ticker_symbol</span> <span class="o">=</span> <span class="s2">"AAPL"</span>
 
 <span class="c1"># Download data using openseries methods</span>
 <span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker_symbol</span><span class="p">)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
 
 <span class="c1"># Create series using openseries from_df method</span>
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">],</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">],</span>
      <span class="n">name</span><span class="o">=</span><span class="n">ticker_symbol</span>
 <span class="p">)</span>
 
 <span class="c1"># Analysis using openseries properties and methods</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;=== </span><span class="si">{</span><span class="n">ticker_symbol</span><span class="si">}</span><span class="s2"> ANALYSIS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Period: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Observations: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"=== </span><span class="si">{</span><span class="n">ticker_symbol</span><span class="si">}</span><span class="s2"> ANALYSIS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Period: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Observations: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Key metrics using openseries properties</span>
 <span class="n">metrics</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;Total Return&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Annual Return&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Volatility&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;95% VaR&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Skewness&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-     <span class="s1">&#39;Kurtosis&#39;</span><span class="p">:</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span>
+     <span class="s1">'Total Return'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Annual Return'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Volatility'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Sharpe Ratio'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Max Drawdown'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'95% VaR'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Skewness'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+     <span class="s1">'Kurtosis'</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span>
 <span class="p">}</span>
 
 <span class="k">for</span> <span class="n">metric</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">metrics</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">metric</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">value</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">metric</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">value</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Export results using openseries to_xlsx method</span>
-<span class="n">filename</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">ticker_symbol</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span><span class="si">}</span><span class="s2">_analysis.xlsx&quot;</span>
+<span class="n">filename</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">ticker_symbol</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span><span class="si">}</span><span class="s2">_analysis.xlsx"</span>
 <span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Results exported to </span><span class="si">{</span><span class="n">filename</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Results exported to </span><span class="si">{</span><span class="n">filename</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Example: Analyze multiple assets</span>
-<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="s2">&quot;TSLA&quot;</span><span class="p">,</span> <span class="s2">&quot;MSFT&quot;</span><span class="p">]</span>
+<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"AAPL"</span><span class="p">,</span> <span class="s2">"TSLA"</span><span class="p">,</span> <span class="s2">"MSFT"</span><span class="p">]</span>
 <span class="k">for</span> <span class="n">ticker_symbol</span> <span class="ow">in</span> <span class="n">tickers</span><span class="p">:</span>
      <span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker_symbol</span><span class="p">)</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;2y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"2y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">ticker_symbol</span><span class="p">)</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">ticker_symbol</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">ticker_symbol</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index 035452ee..56e77f78 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -156,18 +156,18 @@ <h2>Quick Start<a class="headerlink" href="#quick-start" title="Link to this hea
 <span class="kn">import</span><span class="w"> </span><span class="nn">yfinance</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">yf</span>
 
 <span class="c1"># Download data</span>
-<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;^GSPC&quot;</span><span class="p">)</span>
-<span class="n">history</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"^GSPC"</span><span class="p">)</span>
+<span class="n">history</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenTimeSeries</span>
-<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">history</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">&quot;Close&quot;</span><span class="p">])</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">)</span>
+<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">history</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="s2">"Close"</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"S&amp;P 500"</span><span class="p">)</span>
 
 <span class="c1"># Calculate key metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annual Return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Drawdown: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annual Return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Drawdown: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Create interactive plot</span>
 <span class="n">series</span><span class="o">.</span><span class="n">plot_series</span><span class="p">()</span>
diff --git a/docs/build/html/tutorials/advanced_features.html b/docs/build/html/tutorials/advanced_features.html
index ab8eca10..d2a184da 100644
--- a/docs/build/html/tutorials/advanced_features.html
+++ b/docs/build/html/tutorials/advanced_features.html
@@ -136,18 +136,18 @@ <h3>Multi-Factor Model Analysis<a class="headerlink" href="#multi-factor-model-a
 
 <span class="c1"># Load factor data (Fama-French factors would be ideal, using proxies here)</span>
 <span class="n">factor_tickers</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;^GSPC&quot;</span><span class="p">:</span> <span class="s2">&quot;Market&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;^RUT&quot;</span><span class="p">:</span> <span class="s2">&quot;Small Cap&quot;</span><span class="p">,</span>  <span class="c1"># Size factor proxy</span>
-     <span class="s2">&quot;EFA&quot;</span><span class="p">:</span> <span class="s2">&quot;International&quot;</span><span class="p">,</span>  <span class="c1"># International factor</span>
-     <span class="s2">&quot;TLT&quot;</span><span class="p">:</span> <span class="s2">&quot;Bonds&quot;</span>  <span class="c1"># Interest rate factor</span>
+     <span class="s2">"^GSPC"</span><span class="p">:</span> <span class="s2">"Market"</span><span class="p">,</span>
+     <span class="s2">"^RUT"</span><span class="p">:</span> <span class="s2">"Small Cap"</span><span class="p">,</span>  <span class="c1"># Size factor proxy</span>
+     <span class="s2">"EFA"</span><span class="p">:</span> <span class="s2">"International"</span><span class="p">,</span>  <span class="c1"># International factor</span>
+     <span class="s2">"TLT"</span><span class="p">:</span> <span class="s2">"Bonds"</span>  <span class="c1"># Interest rate factor</span>
 <span class="p">}</span>
 
 <span class="c1"># Load factor data</span>
 <span class="n">factor_series</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">factor_tickers</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">factor_series</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
@@ -155,9 +155,9 @@ <h3>Multi-Factor Model Analysis<a class="headerlink" href="#multi-factor-model-a
 <span class="n">factors</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">factor_series</span><span class="p">)</span>
 
 <span class="c1"># Load individual stock for analysis</span>
-<span class="n">stock_data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;AAPL&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
-<span class="n">apple</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">stock_data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">apple</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Apple&quot;</span><span class="p">)</span>
+<span class="n">stock_data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"AAPL"</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
+<span class="n">apple</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">stock_data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">apple</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Apple"</span><span class="p">)</span>
 
 <span class="c1"># Add stock to factor frame for regression</span>
 <span class="n">analysis_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">factor_series</span> <span class="o">+</span> <span class="p">[</span><span class="n">apple</span><span class="p">])</span>
@@ -168,17 +168,17 @@ <h3>Multi-Factor Model Analysis<a class="headerlink" href="#multi-factor-model-a
      <span class="n">dependent_variable_idx</span><span class="o">=-</span><span class="mi">1</span>  <span class="c1"># Apple is the last series (dependent variable)</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MULTI-FACTOR REGRESSION RESULTS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Regression Summary:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">&#39;summary&#39;</span><span class="p">])</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MULTI-FACTOR REGRESSION RESULTS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Regression Summary:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">'summary'</span><span class="p">])</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Factor Loadings (Betas):&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Factor Loadings (Betas):"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">factor_name</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">label</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">factor_series</span><span class="p">]):</span>
-     <span class="n">beta</span> <span class="o">=</span> <span class="n">regression_results</span><span class="p">[</span><span class="s1">&#39;coefficients&#39;</span><span class="p">][</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span>  <span class="c1"># Skip intercept</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">factor_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">beta</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="n">beta</span> <span class="o">=</span> <span class="n">regression_results</span><span class="p">[</span><span class="s1">'coefficients'</span><span class="p">][</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span>  <span class="c1"># Skip intercept</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">factor_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">beta</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">R-squared: </span><span class="si">{</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">&#39;r_squared&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Adjusted R-squared: </span><span class="si">{</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">&#39;adj_r_squared&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">R-squared: </span><span class="si">{</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">'r_squared'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Adjusted R-squared: </span><span class="si">{</span><span class="n">regression_results</span><span class="p">[</span><span class="s1">'adj_r_squared'</span><span class="p">]</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -191,19 +191,19 @@ <h3>Rolling Factor Analysis<a class="headerlink" href="#rolling-factor-analysis"
 <span class="c1"># Calculate rolling beta</span>
 <span class="n">rolling_beta</span> <span class="o">=</span> <span class="n">stock_vs_market</span><span class="o">.</span><span class="n">rolling_beta</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>  <span class="c1"># 1-year rolling</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ROLLING BETA ANALYSIS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Current Beta: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average Beta: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Beta Range: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Beta Volatility: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ROLLING BETA ANALYSIS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Current Beta: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average Beta: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Beta Range: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Beta Volatility: </span><span class="si">{</span><span class="n">rolling_beta</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rolling correlation</span>
 <span class="n">rolling_corr</span> <span class="o">=</span> <span class="n">stock_vs_market</span><span class="o">.</span><span class="n">rolling_corr</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ROLLING CORRELATION ANALYSIS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Current Correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average Correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Correlation Range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ROLLING CORRELATION ANALYSIS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Current Correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average Correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Correlation Range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -222,45 +222,45 @@ <h3>Creating Custom Plots<a class="headerlink" href="#creating-custom-plots" tit
 <span class="c1"># Create a custom subplot figure</span>
 <span class="n">fig</span> <span class="o">=</span> <span class="n">make_subplots</span><span class="p">(</span>
     <span class="n">rows</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">cols</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
-    <span class="n">subplot_titles</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;Price Chart&#39;</span><span class="p">,</span> <span class="s1">&#39;Volume&#39;</span><span class="p">,</span> <span class="s1">&#39;Returns Distribution&#39;</span><span class="p">,</span> <span class="s1">&#39;Drawdown&#39;</span><span class="p">),</span>
-    <span class="n">specs</span><span class="o">=</span><span class="p">[[{</span><span class="s2">&quot;secondary_y&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span> <span class="p">{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;bar&quot;</span><span class="p">}],</span>
-          <span class="p">[{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;histogram&quot;</span><span class="p">},</span> <span class="p">{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;scatter&quot;</span><span class="p">}]]</span>
+    <span class="n">subplot_titles</span><span class="o">=</span><span class="p">(</span><span class="s1">'Price Chart'</span><span class="p">,</span> <span class="s1">'Volume'</span><span class="p">,</span> <span class="s1">'Returns Distribution'</span><span class="p">,</span> <span class="s1">'Drawdown'</span><span class="p">),</span>
+    <span class="n">specs</span><span class="o">=</span><span class="p">[[{</span><span class="s2">"secondary_y"</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span> <span class="p">{</span><span class="s2">"type"</span><span class="p">:</span> <span class="s2">"bar"</span><span class="p">}],</span>
+          <span class="p">[{</span><span class="s2">"type"</span><span class="p">:</span> <span class="s2">"histogram"</span><span class="p">},</span> <span class="p">{</span><span class="s2">"type"</span><span class="p">:</span> <span class="s2">"scatter"</span><span class="p">}]]</span>
 <span class="p">)</span>
 
 <span class="c1"># Add traces (example data)</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">add_trace</span><span class="p">(</span>
-    <span class="n">go</span><span class="o">.</span><span class="n">Scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Price&quot;</span><span class="p">),</span>
+    <span class="n">go</span><span class="o">.</span><span class="n">Scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">11</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">13</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Price"</span><span class="p">),</span>
     <span class="n">row</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">col</span><span class="o">=</span><span class="mi">1</span>
 <span class="p">)</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">add_trace</span><span class="p">(</span>
-    <span class="n">go</span><span class="o">.</span><span class="n">Bar</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">200</span><span class="p">,</span> <span class="mi">150</span><span class="p">,</span> <span class="mi">300</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Volume&quot;</span><span class="p">),</span>
+    <span class="n">go</span><span class="o">.</span><span class="n">Bar</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">200</span><span class="p">,</span> <span class="mi">150</span><span class="p">,</span> <span class="mi">300</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Volume"</span><span class="p">),</span>
     <span class="n">row</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">col</span><span class="o">=</span><span class="mi">2</span>
 <span class="p">)</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">add_trace</span><span class="p">(</span>
-    <span class="n">go</span><span class="o">.</span><span class="n">Histogram</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mf">0.01</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.015</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Returns&quot;</span><span class="p">),</span>
+    <span class="n">go</span><span class="o">.</span><span class="n">Histogram</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mf">0.01</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.015</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Returns"</span><span class="p">),</span>
     <span class="n">row</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">col</span><span class="o">=</span><span class="mi">1</span>
 <span class="p">)</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">add_trace</span><span class="p">(</span>
-    <span class="n">go</span><span class="o">.</span><span class="n">Scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.05</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.03</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Drawdown&quot;</span><span class="p">),</span>
+    <span class="n">go</span><span class="o">.</span><span class="n">Scatter</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.05</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.03</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Drawdown"</span><span class="p">),</span>
     <span class="n">row</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">col</span><span class="o">=</span><span class="mi">2</span>
 <span class="p">)</span>
 
 <span class="c1"># Update layout</span>
-<span class="n">fig</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">height</span><span class="o">=</span><span class="mi">800</span><span class="p">,</span> <span class="n">title_text</span><span class="o">=</span><span class="s2">&quot;Custom Multi-Panel Dashboard&quot;</span><span class="p">)</span>
+<span class="n">fig</span><span class="o">.</span><span class="n">update_layout</span><span class="p">(</span><span class="n">height</span><span class="o">=</span><span class="mi">800</span><span class="p">,</span> <span class="n">title_text</span><span class="o">=</span><span class="s2">"Custom Multi-Panel Dashboard"</span><span class="p">)</span>
 
 <span class="c1"># Export to responsive HTML</span>
 <span class="n">output_path</span> <span class="o">=</span> <span class="n">export_plotly_figure</span><span class="p">(</span>
     <span class="n">figure</span><span class="o">=</span><span class="n">fig</span><span class="p">,</span>
-    <span class="n">fig_config</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;responsive&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
-    <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;file&quot;</span><span class="p">,</span>
-    <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;custom_dashboard.html&quot;</span><span class="p">,</span>
-    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">&quot;cdn&quot;</span><span class="p">,</span>
-    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">&quot;output/custom_dashboard.html&quot;</span><span class="p">),</span>
-    <span class="n">title</span><span class="o">=</span><span class="s2">&quot;Custom Financial Dashboard&quot;</span><span class="p">,</span>
+    <span class="n">fig_config</span><span class="o">=</span><span class="p">{</span><span class="s2">"responsive"</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
+    <span class="n">output_type</span><span class="o">=</span><span class="s2">"file"</span><span class="p">,</span>
+    <span class="n">filename</span><span class="o">=</span><span class="s2">"custom_dashboard.html"</span><span class="p">,</span>
+    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">"cdn"</span><span class="p">,</span>
+    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">"output/custom_dashboard.html"</span><span class="p">),</span>
+    <span class="n">title</span><span class="o">=</span><span class="s2">"Custom Financial Dashboard"</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Dashboard saved to: </span><span class="si">{</span><span class="n">output_path</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Dashboard saved to: </span><span class="si">{</span><span class="n">output_path</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -274,27 +274,27 @@ <h3>Using with Plotly Express<a class="headerlink" href="#using-with-plotly-expr
 
 <span class="c1"># Create sample data</span>
 <span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
-    <span class="s1">&#39;Date&#39;</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">&#39;2020-01-01&#39;</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">100</span><span class="p">),</span>
-    <span class="s1">&#39;Asset_A&#39;</span><span class="p">:</span> <span class="mi">100</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span> <span class="o">*</span> <span class="mf">0.1</span><span class="p">,</span>
-    <span class="s1">&#39;Asset_B&#39;</span><span class="p">:</span> <span class="mi">100</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span> <span class="o">*</span> <span class="mf">0.15</span><span class="p">,</span>
+    <span class="s1">'Date'</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">'2020-01-01'</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">100</span><span class="p">),</span>
+    <span class="s1">'Asset_A'</span><span class="p">:</span> <span class="mi">100</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span> <span class="o">*</span> <span class="mf">0.1</span><span class="p">,</span>
+    <span class="s1">'Asset_B'</span><span class="p">:</span> <span class="mi">100</span> <span class="o">+</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span><span class="o">.</span><span class="n">cumsum</span><span class="p">()</span> <span class="o">*</span> <span class="mf">0.15</span><span class="p">,</span>
 <span class="p">})</span>
 
 <span class="c1"># Create a Plotly Express figure</span>
 <span class="n">fig</span> <span class="o">=</span> <span class="n">px</span><span class="o">.</span><span class="n">line</span><span class="p">(</span>
-    <span class="n">df</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">&#39;Date&#39;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Asset_A&#39;</span><span class="p">,</span> <span class="s1">&#39;Asset_B&#39;</span><span class="p">],</span>
-    <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Asset Comparison&#39;</span><span class="p">,</span>
-    <span class="n">labels</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;value&#39;</span><span class="p">:</span> <span class="s1">&#39;Price&#39;</span><span class="p">,</span> <span class="s1">&#39;variable&#39;</span><span class="p">:</span> <span class="s1">&#39;Asset&#39;</span><span class="p">}</span>
+    <span class="n">df</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="s1">'Date'</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="s1">'Asset_A'</span><span class="p">,</span> <span class="s1">'Asset_B'</span><span class="p">],</span>
+    <span class="n">title</span><span class="o">=</span><span class="s1">'Asset Comparison'</span><span class="p">,</span>
+    <span class="n">labels</span><span class="o">=</span><span class="p">{</span><span class="s1">'value'</span><span class="p">:</span> <span class="s1">'Price'</span><span class="p">,</span> <span class="s1">'variable'</span><span class="p">:</span> <span class="s1">'Asset'</span><span class="p">}</span>
 <span class="p">)</span>
 
 <span class="c1"># Export with responsive HTML</span>
 <span class="n">export_plotly_figure</span><span class="p">(</span>
     <span class="n">figure</span><span class="o">=</span><span class="n">fig</span><span class="p">,</span>
-    <span class="n">fig_config</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;responsive&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">&quot;displayModeBar&quot;</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
-    <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;file&quot;</span><span class="p">,</span>
-    <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;asset_comparison.html&quot;</span><span class="p">,</span>
-    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">&quot;cdn&quot;</span><span class="p">,</span>
-    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">&quot;output/asset_comparison.html&quot;</span><span class="p">),</span>
-    <span class="n">title</span><span class="o">=</span><span class="s2">&quot;Asset Price Comparison&quot;</span><span class="p">,</span>
+    <span class="n">fig_config</span><span class="o">=</span><span class="p">{</span><span class="s2">"responsive"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"displayModeBar"</span><span class="p">:</span> <span class="kc">True</span><span class="p">},</span>
+    <span class="n">output_type</span><span class="o">=</span><span class="s2">"file"</span><span class="p">,</span>
+    <span class="n">filename</span><span class="o">=</span><span class="s2">"asset_comparison.html"</span><span class="p">,</span>
+    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">"cdn"</span><span class="p">,</span>
+    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">"output/asset_comparison.html"</span><span class="p">),</span>
+    <span class="n">title</span><span class="o">=</span><span class="s2">"Asset Price Comparison"</span><span class="p">,</span>
     <span class="n">auto_open</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
 <span class="p">)</span>
 </pre></div>
@@ -313,10 +313,10 @@ <h3>Inline HTML Output<a class="headerlink" href="#inline-html-output" title="Li
 <span class="n">html_div</span> <span class="o">=</span> <span class="n">export_plotly_figure</span><span class="p">(</span>
     <span class="n">figure</span><span class="o">=</span><span class="n">fig</span><span class="p">,</span>
     <span class="n">fig_config</span><span class="o">=</span><span class="p">{},</span>
-    <span class="n">output_type</span><span class="o">=</span><span class="s2">&quot;div&quot;</span><span class="p">,</span>
-    <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;my_plot.html&quot;</span><span class="p">,</span>
-    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">&quot;cdn&quot;</span><span class="p">,</span>
-    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">&quot;dummy.html&quot;</span><span class="p">),</span>  <span class="c1"># Ignored for div output</span>
+    <span class="n">output_type</span><span class="o">=</span><span class="s2">"div"</span><span class="p">,</span>
+    <span class="n">filename</span><span class="o">=</span><span class="s2">"my_plot.html"</span><span class="p">,</span>
+    <span class="n">include_plotlyjs</span><span class="o">=</span><span class="s2">"cdn"</span><span class="p">,</span>
+    <span class="n">plotfile</span><span class="o">=</span><span class="n">Path</span><span class="p">(</span><span class="s2">"dummy.html"</span><span class="p">),</span>  <span class="c1"># Ignored for div output</span>
 <span class="p">)</span>
 
 <span class="c1"># html_div can now be embedded in HTML documents</span>
diff --git a/docs/build/html/tutorials/basic_analysis.html b/docs/build/html/tutorials/basic_analysis.html
index da40b8cd..916f9ae9 100644
--- a/docs/build/html/tutorials/basic_analysis.html
+++ b/docs/build/html/tutorials/basic_analysis.html
@@ -141,19 +141,19 @@ <h2>Setting Up<a class="headerlink" href="#setting-up" title="Link to this headi
 <span class="kn">from</span><span class="w"> </span><span class="nn">datetime</span><span class="w"> </span><span class="kn">import</span> <span class="n">date</span><span class="p">,</span> <span class="n">datetime</span>
 
 <span class="c1"># Download S&amp;P 500 data for the last 5 years</span>
-<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;^GSPC&quot;</span><span class="p">)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"^GSPC"</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenTimeSeries</span>
 <span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
 <span class="p">)</span>
 
 <span class="c1"># Set a descriptive label</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500 Index&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"S&amp;P 500 Index"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Date range: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -162,20 +162,20 @@ <h2>Basic Performance Metrics<a class="headerlink" href="#basic-performance-metr
 <p>Let’s calculate the fundamental performance metrics:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Total return over the period</span>
 <span class="n">total_return</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">value_ret</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">total_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">total_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Annualized return (CAGR)</span>
 <span class="n">annual_return</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return (CAGR): </span><span class="si">{</span><span class="n">annual_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return (CAGR): </span><span class="si">{</span><span class="n">annual_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Arithmetic mean return</span>
 <span class="n">arithmetic_return</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">arithmetic_ret</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Arithmetic Mean Return: </span><span class="si">{</span><span class="n">arithmetic_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Arithmetic Mean Return: </span><span class="si">{</span><span class="n">arithmetic_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Time period analysis</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Investment period: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">yearfrac</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> years&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Periods per year: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Investment period: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">yearfrac</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> years"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Periods per year: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -184,23 +184,23 @@ <h2>Risk Analysis<a class="headerlink" href="#risk-analysis" title="Link to this
 <p>Now let’s examine the risk characteristics:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Volatility (annualized standard deviation)</span>
 <span class="n">volatility</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">vol</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">volatility</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">volatility</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Downside deviation (volatility of negative returns only)</span>
 <span class="n">downside_vol</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">downside_deviation</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Downside Deviation: </span><span class="si">{</span><span class="n">downside_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Downside Deviation: </span><span class="si">{</span><span class="n">downside_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Value at Risk (95% confidence level)</span>
 <span class="n">var_95</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">var_down</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% Value at Risk (daily): </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% Value at Risk (daily): </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Conditional Value at Risk (Expected Shortfall)</span>
 <span class="n">cvar_95</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR (daily): </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR (daily): </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Maximum single-day loss</span>
 <span class="n">worst_day</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">worst</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst single day: </span><span class="si">{</span><span class="n">worst_day</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst single day: </span><span class="si">{</span><span class="n">worst_day</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -209,19 +209,19 @@ <h2>Risk-Adjusted Returns<a class="headerlink" href="#risk-adjusted-returns" tit
 <p>Calculate risk-adjusted performance metrics:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Sharpe Ratio (return per unit of total risk)</span>
 <span class="n">sharpe_ratio</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Sortino Ratio (return per unit of downside risk)</span>
 <span class="n">sortino_ratio</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">sortino_ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Kappa-3 Ratio (penalizes larger downside deviations more)</span>
 <span class="n">kappa3_ratio</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">kappa3_ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kappa-3 Ratio: </span><span class="si">{</span><span class="n">kappa3_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kappa-3 Ratio: </span><span class="si">{</span><span class="n">kappa3_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Omega Ratio</span>
 <span class="n">omega_ratio</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">omega_ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Omega Ratio: </span><span class="si">{</span><span class="n">omega_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Omega Ratio: </span><span class="si">{</span><span class="n">omega_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -231,8 +231,8 @@ <h2>Drawdown Analysis<a class="headerlink" href="#drawdown-analysis" title="Link
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Maximum drawdown</span>
 <span class="n">max_drawdown</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span>
 <span class="n">max_dd_date</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown_date</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Drawdown Date: </span><span class="si">{</span><span class="n">max_dd_date</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Drawdown Date: </span><span class="si">{</span><span class="n">max_dd_date</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Create drawdown series for visualization (modifies original)</span>
 <span class="n">sp500</span><span class="o">.</span><span class="n">to_drawdown_series</span><span class="p">()</span>
@@ -243,7 +243,7 @@ <h2>Drawdown Analysis<a class="headerlink" href="#drawdown-analysis" title="Link
 
 <span class="c1"># Worst calendar year drawdown</span>
 <span class="n">worst_year_dd</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown_cal_year</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Calendar Year Drawdown: </span><span class="si">{</span><span class="n">worst_year_dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Calendar Year Drawdown: </span><span class="si">{</span><span class="n">worst_year_dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -255,30 +255,30 @@ <h2>Distribution Analysis<a class="headerlink" href="#distribution-analysis" tit
 
 <span class="c1"># Note: value_to_ret() modifies the original series in place</span>
 <span class="c1"># Restore the original series for further analysis</span>
-<span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500 Index&quot;</span><span class="p">)</span>
+<span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"S&amp;P 500 Index"</span><span class="p">)</span>
 
 <span class="c1"># Skewness (asymmetry of the distribution)</span>
 <span class="n">skewness</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">skew</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Skewness: </span><span class="si">{</span><span class="n">skewness</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Skewness: </span><span class="si">{</span><span class="n">skewness</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">if</span> <span class="n">skewness</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  → Negative skew: more extreme negative returns&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  → Negative skew: more extreme negative returns"</span><span class="p">)</span>
 <span class="k">elif</span> <span class="n">skewness</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  → Positive skew: more extreme positive returns&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  → Positive skew: more extreme positive returns"</span><span class="p">)</span>
 
 <span class="c1"># Kurtosis (tail heaviness)</span>
 <span class="n">kurtosis</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">kurtosis</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kurtosis: </span><span class="si">{</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kurtosis: </span><span class="si">{</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">if</span> <span class="n">kurtosis</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  → Fat tails: more extreme returns than normal distribution&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  → Fat tails: more extreme returns than normal distribution"</span><span class="p">)</span>
 
 <span class="c1"># Percentage of positive days</span>
 <span class="n">positive_share</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">positive_share</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Positive Days: </span><span class="si">{</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Positive Days: </span><span class="si">{</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Current Z-score (how unusual is the last return?)</span>
 <span class="n">z_score</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">z_score</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Last Return Z-score: </span><span class="si">{</span><span class="n">z_score</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Last Return Z-score: </span><span class="si">{</span><span class="n">z_score</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -286,22 +286,22 @@ <h2>Distribution Analysis<a class="headerlink" href="#distribution-analysis" tit
 <h2>Monthly and Annual Analysis<a class="headerlink" href="#monthly-and-annual-analysis" title="Link to this heading"></a></h2>
 <p>Break down performance by different time periods:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Resample to monthly data (modifies original)</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monthly observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monthly observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Monthly metrics</span>
 <span class="n">monthly_return</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span>
 <span class="n">monthly_vol</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">vol</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monthly Return (annualized): </span><span class="si">{</span><span class="n">monthly_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monthly Volatility (annualized): </span><span class="si">{</span><span class="n">monthly_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monthly Return (annualized): </span><span class="si">{</span><span class="n">monthly_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monthly Volatility (annualized): </span><span class="si">{</span><span class="n">monthly_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Worst month</span>
 <span class="n">worst_month</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">worst_month</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Month: </span><span class="si">{</span><span class="n">worst_month</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Month: </span><span class="si">{</span><span class="n">worst_month</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Annual data (modifies original)</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BYE&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annual observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BYE"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annual observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 <section id="calendar-year-returns">
@@ -312,7 +312,7 @@ <h3>Calendar Year Returns<a class="headerlink" href="#calendar-year-returns" tit
 <span class="k">for</span> <span class="n">year</span> <span class="ow">in</span> <span class="n">years</span><span class="p">:</span>
      <span class="c1"># This may fail if no data exists for the year</span>
      <span class="n">year_return</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">value_ret_calendar_period</span><span class="p">(</span><span class="n">year</span><span class="o">=</span><span class="n">year</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">year</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">year_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">year</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">year_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -322,20 +322,20 @@ <h2>Rolling Analysis<a class="headerlink" href="#rolling-analysis" title="Link t
 <p>Analyze how metrics change over time:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># 252-day (1-year) rolling volatility</span>
 <span class="n">rolling_vol</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">rolling_vol</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling volatility calculated for </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">rolling_vol</span><span class="p">)</span><span class="si">}</span><span class="s2"> periods&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling volatility calculated for </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">rolling_vol</span><span class="p">)</span><span class="si">}</span><span class="s2"> periods"</span><span class="p">)</span>
 
 <span class="c1"># 30-day rolling returns</span>
 <span class="n">rolling_returns</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">rolling_return</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">30</span><span class="p">)</span>
 
 <span class="c1"># Plot rolling volatility</span>
 <span class="c1"># Convert to OpenTimeSeries for plotting</span>
-<span class="n">vol_dates</span> <span class="o">=</span> <span class="n">rolling_vol</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%Y-%m-</span><span class="si">%d</span><span class="s1">&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
+<span class="n">vol_dates</span> <span class="o">=</span> <span class="n">rolling_vol</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">'%Y-%m-</span><span class="si">%d</span><span class="s1">'</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
 <span class="n">vol_values</span> <span class="o">=</span> <span class="n">rolling_vol</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
 
 <span class="n">vol_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
      <span class="n">dates</span><span class="o">=</span><span class="n">vol_dates</span><span class="p">,</span>
      <span class="n">values</span><span class="o">=</span><span class="n">vol_values</span><span class="p">,</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Rolling Volatility&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Rolling Volatility"</span>
 <span class="p">)</span>
 
 <span class="n">vol_series</span><span class="o">.</span><span class="n">plot_series</span><span class="p">()</span>
@@ -347,12 +347,12 @@ <h2>Comprehensive Report<a class="headerlink" href="#comprehensive-report" title
 <p>Get all metrics at once:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Generate comprehensive metrics report</span>
 <span class="n">all_metrics</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== COMPREHENSIVE ANALYSIS REPORT ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== COMPREHENSIVE ANALYSIS REPORT ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">all_metrics</span><span class="p">)</span>
 
 <span class="c1"># Save to Excel for further analysis</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">&quot;sp500_analysis.xlsx&quot;</span><span class="p">)</span>
-<span class="n">all_metrics</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">excel_writer</span><span class="o">=</span><span class="s2">&quot;sp500_metrics.xlsx&quot;</span><span class="p">,</span> <span class="n">engine</span><span class="o">=</span><span class="s2">&quot;openpyxl&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">"sp500_analysis.xlsx"</span><span class="p">)</span>
+<span class="n">all_metrics</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">excel_writer</span><span class="o">=</span><span class="s2">"sp500_metrics.xlsx"</span><span class="p">,</span> <span class="n">engine</span><span class="o">=</span><span class="s2">"openpyxl"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -378,26 +378,26 @@ <h2>Visualization<a class="headerlink" href="#visualization" title="Link to this
 <h2>Comparison with Benchmark<a class="headerlink" href="#comparison-with-benchmark" title="Link to this heading"></a></h2>
 <p>Let’s compare with a bond index:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Download bond data (10-year Treasury)</span>
-<span class="n">bond_ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;^TNX&quot;</span><span class="p">)</span>
-<span class="n">bond_data</span> <span class="o">=</span> <span class="n">bond_ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+<span class="n">bond_ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"^TNX"</span><span class="p">)</span>
+<span class="n">bond_data</span> <span class="o">=</span> <span class="n">bond_ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
 
 <span class="c1"># Create bond series (using yield data)</span>
 <span class="n">bonds</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">bond_data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">bond_data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
 <span class="p">)</span>
-<span class="n">bonds</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;10Y Treasury Yield&quot;</span><span class="p">)</span>
+<span class="n">bonds</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"10Y Treasury Yield"</span><span class="p">)</span>
 
 <span class="c1"># Create frame for comparison</span>
 <span class="n">comparison_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="p">[</span><span class="n">sp500</span><span class="p">,</span> <span class="n">bonds</span><span class="p">])</span>
 
 <span class="c1"># Compare metrics</span>
 <span class="n">comparison_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ASSET COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ASSET COMPARISON ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">comparison_metrics</span><span class="p">)</span>
 
 <span class="c1"># Calculate correlation</span>
 <span class="n">correlation_matrix</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">correl_matrix</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -410,48 +410,48 @@ <h2>Advanced Risk Metrics<a class="headerlink" href="#advanced-risk-metrics" tit
 <span class="n">var_95</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">var_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.95</span><span class="p">)</span>
 <span class="n">var_99</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">var_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.99</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;90% VaR: </span><span class="si">{</span><span class="n">var_90</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR: </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;99% VaR: </span><span class="si">{</span><span class="n">var_99</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"90% VaR: </span><span class="si">{</span><span class="n">var_90</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR: </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"99% VaR: </span><span class="si">{</span><span class="n">var_99</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># CVaR at different confidence levels</span>
 <span class="n">cvar_90</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.90</span><span class="p">)</span>
 <span class="n">cvar_95</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.95</span><span class="p">)</span>
 <span class="n">cvar_99</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.99</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;90% CVaR: </span><span class="si">{</span><span class="n">cvar_90</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR: </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;99% CVaR: </span><span class="si">{</span><span class="n">cvar_99</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"90% CVaR: </span><span class="si">{</span><span class="n">cvar_90</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR: </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"99% CVaR: </span><span class="si">{</span><span class="n">cvar_99</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Implied volatility from VaR (assuming normal distribution)</span>
 <span class="n">vol_from_var</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">vol_from_var</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility implied from VaR: </span><span class="si">{</span><span class="n">vol_from_var</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Actual volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility implied from VaR: </span><span class="si">{</span><span class="n">vol_from_var</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Actual volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="summary-and-interpretation">
 <h2>Summary and Interpretation<a class="headerlink" href="#summary-and-interpretation" title="Link to this heading"></a></h2>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== INVESTMENT SUMMARY ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Asset: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Period: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== INVESTMENT SUMMARY ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Asset: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Period: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Risk assessment</span>
 <span class="k">if</span> <span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span> <span class="o">&gt;</span> <span class="mf">1.0</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;✓ Good risk-adjusted returns (Sharpe &gt; 1.0)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"✓ Good risk-adjusted returns (Sharpe &gt; 1.0)"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;⚠ Moderate risk-adjusted returns (Sharpe &lt; 1.0)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"⚠ Moderate risk-adjusted returns (Sharpe &lt; 1.0)"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mf">0.20</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;✓ Moderate maximum drawdown (&lt; 20%)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"✓ Moderate maximum drawdown (&lt; 20%)"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;⚠ Significant maximum drawdown (&gt; 20%)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"⚠ Significant maximum drawdown (&gt; 20%)"</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>This tutorial provides a comprehensive foundation for financial analysis using openseries. You can adapt these techniques for any financial time series data.</p>
diff --git a/docs/build/html/tutorials/portfolio_analysis.html b/docs/build/html/tutorials/portfolio_analysis.html
index d0a1366b..5fd7ee4d 100644
--- a/docs/build/html/tutorials/portfolio_analysis.html
+++ b/docs/build/html/tutorials/portfolio_analysis.html
@@ -151,31 +151,31 @@ <h2>Setting Up the Data<a class="headerlink" href="#setting-up-the-data" title="
 
 <span class="c1"># Define our universe of assets</span>
 <span class="n">tickers</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;^GSPC&quot;</span><span class="p">:</span> <span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;EFA&quot;</span><span class="p">:</span> <span class="s2">&quot;EAFE International&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;EEM&quot;</span><span class="p">:</span> <span class="s2">&quot;Emerging Markets&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;AGG&quot;</span><span class="p">:</span> <span class="s2">&quot;US Aggregate Bonds&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;VNQ&quot;</span><span class="p">:</span> <span class="s2">&quot;US REITs&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;GLD&quot;</span><span class="p">:</span> <span class="s2">&quot;Gold&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;DBC&quot;</span><span class="p">:</span> <span class="s2">&quot;Commodities&quot;</span>
+     <span class="s2">"^GSPC"</span><span class="p">:</span> <span class="s2">"S&amp;P 500"</span><span class="p">,</span>
+     <span class="s2">"EFA"</span><span class="p">:</span> <span class="s2">"EAFE International"</span><span class="p">,</span>
+     <span class="s2">"EEM"</span><span class="p">:</span> <span class="s2">"Emerging Markets"</span><span class="p">,</span>
+     <span class="s2">"AGG"</span><span class="p">:</span> <span class="s2">"US Aggregate Bonds"</span><span class="p">,</span>
+     <span class="s2">"VNQ"</span><span class="p">:</span> <span class="s2">"US REITs"</span><span class="p">,</span>
+     <span class="s2">"GLD"</span><span class="p">:</span> <span class="s2">"Gold"</span><span class="p">,</span>
+     <span class="s2">"DBC"</span><span class="p">:</span> <span class="s2">"Commodities"</span>
 <span class="p">}</span>
 
 <span class="c1"># Download 5 years of data</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">tickers</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;5y&quot;</span><span class="p">)</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"5y"</span><span class="p">)</span>
      <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
      <span class="p">)</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenFrame</span>
 <span class="n">assets</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">series_list</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Created frame with </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Common date range: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Created frame with </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2"> assets"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Common date range: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -184,22 +184,22 @@ <h2>Asset Analysis<a class="headerlink" href="#asset-analysis" title="Link to th
 <p>First, let’s analyze the individual assets:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Get metrics for all assets</span>
 <span class="n">asset_metrics</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== INDIVIDUAL ASSET METRICS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"=== INDIVIDUAL ASSET METRICS ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">asset_metrics</span><span class="p">)</span>
 
 <span class="c1"># Key metrics comparison</span>
-<span class="n">returns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">]</span>
-<span class="n">volatilities</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span>
-<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Return vol ratio&#39;</span><span class="p">]</span>
-<span class="n">max_drawdowns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Max drawdown&#39;</span><span class="p">]</span>
+<span class="n">returns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">]</span>
+<span class="n">volatilities</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span>
+<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Return vol ratio'</span><span class="p">]</span>
+<span class="n">max_drawdowns</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Max drawdown'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ASSET COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ASSET COMPARISON ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset</span> <span class="ow">in</span> <span class="n">returns</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Annual Return: </span><span class="si">{</span><span class="n">returns</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">volatilities</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Max Drawdown: </span><span class="si">{</span><span class="n">max_drawdowns</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Annual Return: </span><span class="si">{</span><span class="n">returns</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">volatilities</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Max Drawdown: </span><span class="si">{</span><span class="n">max_drawdowns</span><span class="p">[</span><span class="n">asset</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -208,24 +208,24 @@ <h2>Correlation Analysis<a class="headerlink" href="#correlation-analysis" title
 <p>Understanding correlations is crucial for portfolio construction:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Calculate correlation matrix</span>
 <span class="n">correlation_matrix</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">correl_matrix</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== CORRELATION MATRIX ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
 
 <span class="c1"># Identify highly correlated pairs</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== HIGHLY CORRELATED PAIRS (&gt;0.7) ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== HIGHLY CORRELATED PAIRS (&gt;0.7) ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="o">.</span><span class="n">columns</span><span class="p">)):</span>
      <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">correlation_matrix</span><span class="o">.</span><span class="n">columns</span><span class="p">)):</span>
           <span class="n">corr</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">]</span>
           <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">corr</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mf">0.7</span><span class="p">:</span>
                 <span class="n">asset1</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
                 <span class="n">asset2</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">j</span><span class="p">]</span>
-                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset1</span><span class="si">}</span><span class="s2"> - </span><span class="si">{</span><span class="n">asset2</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Average correlation with other assets</span>
 <span class="n">avg_correlations</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== AVERAGE CORRELATIONS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== AVERAGE CORRELATIONS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">asset</span><span class="p">,</span> <span class="n">avg_corr</span> <span class="ow">in</span> <span class="n">avg_correlations</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">avg_corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">avg_corr</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -235,12 +235,12 @@ <h2>Simple Portfolio Construction<a class="headerlink" href="#simple-portfolio-c
 <section id="equal-weight-portfolio">
 <h3>Equal Weight Portfolio<a class="headerlink" href="#equal-weight-portfolio" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Create equal-weighted portfolio using native weight_strat</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight Portfolio&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight Portfolio"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">equal_weight_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Sharpe: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Sharpe: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -251,24 +251,24 @@ <h3>Custom Weight Portfolio<a class="headerlink" href="#custom-weight-portfolio"
 <span class="n">custom_weights</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.50</span><span class="p">,</span> <span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.10</span><span class="p">,</span> <span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.03</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">]</span>
 
 <span class="n">assets</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="n">custom_weights</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Custom Weighted&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Custom Weighted"</span><span class="p">)</span>
 <span class="n">custom_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Custom Portfolio Return: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Custom Portfolio Volatility: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Custom Portfolio Sharpe: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Custom Portfolio Return: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Custom Portfolio Volatility: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Custom Portfolio Sharpe: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="risk-parity-portfolio">
 <h3>Risk Parity Portfolio<a class="headerlink" href="#risk-parity-portfolio" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Use native inverse volatility weighting (risk parity)</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Risk Parity&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;inv_vol&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Risk Parity"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"inv_vol"</span><span class="p">)</span>
 <span class="n">risk_parity_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Risk Parity Portfolio Return: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Risk Parity Portfolio Volatility: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Risk Parity Portfolio Sharpe: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Risk Parity Portfolio Return: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Risk Parity Portfolio Volatility: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Risk Parity Portfolio Sharpe: </span><span class="si">{</span><span class="n">risk_parity_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -282,14 +282,14 @@ <h4>Maximum Diversification Strategy<a class="headerlink" href="#maximum-diversi
 
 <span class="c1"># This may fail with MaxDiversificationNaNError or MaxDiversificationNegativeWeightsError</span>
 <span class="n">max_div_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Maximum Diversification&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;max_div&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Maximum Diversification"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"max_div"</span>
 <span class="p">)</span>
 <span class="n">max_div_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">max_div_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Diversification Return: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Diversification Volatility: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Diversification Sharpe: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Diversification Return: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Diversification Volatility: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Diversification Sharpe: </span><span class="si">{</span><span class="n">max_div_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -298,14 +298,14 @@ <h4>Minimum Volatility Overweight Strategy<a class="headerlink" href="#minimum-v
 <p>The minimum volatility overweight strategy overweights the least volatile asset:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># This may fail with various exceptions</span>
 <span class="n">min_vol_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Min Vol Overweight&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;min_vol_overweight&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Min Vol Overweight"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"min_vol_overweight"</span>
 <span class="p">)</span>
 <span class="n">min_vol_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">min_vol_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Min Vol Overweight Return: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Min Vol Overweight Volatility: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Min Vol Overweight Sharpe: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Min Vol Overweight Return: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Min Vol Overweight Volatility: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Min Vol Overweight Sharpe: </span><span class="si">{</span><span class="n">min_vol_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -313,10 +313,10 @@ <h4>Minimum Volatility Overweight Strategy<a class="headerlink" href="#minimum-v
 <h4>Strategy Comparison with Error Handling<a class="headerlink" href="#strategy-comparison-with-error-handling" title="Link to this heading"></a></h4>
 <p>When comparing multiple strategies, it’s important to handle potential failures gracefully:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">strategies</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;Equal Weight&#39;</span><span class="p">:</span> <span class="s1">&#39;eq_weights&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Risk Parity&#39;</span><span class="p">:</span> <span class="s1">&#39;inv_vol&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Max Diversification&#39;</span><span class="p">:</span> <span class="s1">&#39;max_div&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;Min Vol Overweight&#39;</span><span class="p">:</span> <span class="s1">&#39;min_vol_overweight&#39;</span>
+     <span class="s1">'Equal Weight'</span><span class="p">:</span> <span class="s1">'eq_weights'</span><span class="p">,</span>
+     <span class="s1">'Risk Parity'</span><span class="p">:</span> <span class="s1">'inv_vol'</span><span class="p">,</span>
+     <span class="s1">'Max Diversification'</span><span class="p">:</span> <span class="s1">'max_div'</span><span class="p">,</span>
+     <span class="s1">'Min Vol Overweight'</span><span class="p">:</span> <span class="s1">'min_vol_overweight'</span>
 <span class="p">}</span>
 
 <span class="n">results</span> <span class="o">=</span> <span class="p">{}</span>
@@ -325,19 +325,19 @@ <h4>Strategy Comparison with Error Handling<a class="headerlink" href="#strategy
      <span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="n">strategy</span><span class="p">)</span>
      <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
      <span class="n">results</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
-          <span class="s1">&#39;Return&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
-          <span class="s1">&#39;Volatility&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
-          <span class="s1">&#39;Sharpe&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span>
+          <span class="s1">'Return'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="p">,</span>
+          <span class="s1">'Volatility'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
+          <span class="s1">'Sharpe'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span>
      <span class="p">}</span>
 
 <span class="k">if</span> <span class="n">results</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== STRATEGY COMPARISON ===&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== STRATEGY COMPARISON ==="</span><span class="p">)</span>
      <span class="k">for</span> <span class="n">strategy_name</span><span class="p">,</span> <span class="n">metrics</span> <span class="ow">in</span> <span class="n">results</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">strategy_name</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;return&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;volatility&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;max_drawdown&#39;</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">strategy_name</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'return'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'volatility'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+         <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Max Drawdown: </span><span class="si">{</span><span class="n">metrics</span><span class="p">[</span><span class="s1">'max_drawdown'</span><span class="p">]</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -356,25 +356,25 @@ <h3>Efficient Frontier<a class="headerlink" href="#efficient-frontier" title="Li
      <span class="n">seed</span><span class="o">=</span><span class="mi">42</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Efficient frontier calculated successfully&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of frontier points: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frontier_df</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of simulated portfolios: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulated_df</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Efficient frontier calculated successfully"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of frontier points: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frontier_df</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of simulated portfolios: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulated_df</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Find maximum Sharpe ratio portfolio</span>
-<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span> <span class="o">/</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span>
+<span class="n">sharpe_ratios</span> <span class="o">=</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span> <span class="o">/</span> <span class="n">frontier_df</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span>
 <span class="n">max_sharpe_idx</span> <span class="o">=</span> <span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">idxmax</span><span class="p">()</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MAXIMUM SHARPE RATIO PORTFOLIO ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Expected Return: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MAXIMUM SHARPE RATIO PORTFOLIO ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Expected Return: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">'ret'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility: </span><span class="si">{</span><span class="n">frontier_df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">][</span><span class="s1">'stdev'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">max_sharpe_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Get optimal weights</span>
 <span class="n">optimal_weights</span> <span class="o">=</span> <span class="n">optimal_portfolio</span><span class="p">[</span><span class="o">-</span><span class="nb">len</span><span class="p">(</span><span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">):]</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Optimal Weights:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Optimal Weights:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">weight</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">optimal_weights</span><span class="p">):</span>
      <span class="n">asset_name</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">label</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">asset_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -388,21 +388,21 @@ <h3>Monte Carlo Portfolio Simulation<a class="headerlink" href="#monte-carlo-por
      <span class="n">seed</span><span class="o">=</span><span class="mi">42</span>
 <span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulation_results</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Simulated </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">simulation_results</span><span class="p">)</span><span class="si">}</span><span class="s2"> random portfolios"</span><span class="p">)</span>
 
 <span class="c1"># Find best performing portfolios</span>
-<span class="n">sim_sharpe_ratios</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span> <span class="o">/</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span>
+<span class="n">sim_sharpe_ratios</span> <span class="o">=</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span> <span class="o">/</span> <span class="n">simulation_results</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span>
 
 <span class="c1"># Top 5 Sharpe ratios</span>
 <span class="n">sorted_indices</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sim_sharpe_ratios</span><span class="p">)),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">i</span><span class="p">:</span> <span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 <span class="n">top_indices</span> <span class="o">=</span> <span class="n">sorted_indices</span><span class="p">[:</span><span class="mi">5</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== TOP 5 SIMULATED PORTFOLIOS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== TOP 5 SIMULATED PORTFOLIOS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">idx</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">top_indices</span><span class="p">,</span> <span class="mi">1</span><span class="p">):</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Rank </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">simulation_results</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">simulation_results</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Sharpe: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Rank </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">simulation_results</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="s1">'ret'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">simulation_results</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="s1">'stdev'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Sharpe: </span><span class="si">{</span><span class="n">sim_sharpe_ratios</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -421,10 +421,10 @@ <h2>Portfolio Comparison<a class="headerlink" href="#portfolio-comparison" title
 <span class="n">portfolio_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 
 <span class="c1"># Focus on key metrics</span>
-<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">portfolio_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Return vol ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max drawdown&#39;</span><span class="p">]]</span>
-<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Annual Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Max Drawdown&#39;</span><span class="p">]</span>
+<span class="n">key_metrics</span> <span class="o">=</span> <span class="n">portfolio_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="s1">'Geometric return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Return vol ratio'</span><span class="p">,</span> <span class="s1">'Max drawdown'</span><span class="p">]]</span>
+<span class="n">key_metrics</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'Annual Return'</span><span class="p">,</span> <span class="s1">'Volatility'</span><span class="p">,</span> <span class="s1">'Sharpe Ratio'</span><span class="p">,</span> <span class="s1">'Max Drawdown'</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== PORTFOLIO COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== PORTFOLIO COMPARISON ==="</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">((</span><span class="n">key_metrics</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">2</span><span class="p">))</span>  <span class="c1"># Convert to percentages</span>
 </pre></div>
 </div>
@@ -434,21 +434,21 @@ <h2>Risk Attribution<a class="headerlink" href="#risk-attribution" title="Link t
 <p>Analyze the risk contribution of each asset:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Calculate portfolio statistics using openseries methods</span>
 <span class="c1"># Create equal weight portfolio</span>
-<span class="n">equal_weight_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">equal_weight_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">equal_weight_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">equal_weight_portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK ATTRIBUTION (Equal Weight Portfolio) ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK ATTRIBUTION (Equal Weight Portfolio) ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Individual asset contributions can be analyzed using openseries properties</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">series</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">):</span>
     <span class="n">weight</span> <span class="o">=</span> <span class="n">equal_weights</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
     <span class="n">asset_vol</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">vol</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Individual Volatility: </span><span class="si">{</span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weighted Contribution: </span><span class="si">{</span><span class="n">weight</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Individual Volatility: </span><span class="si">{</span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weighted Contribution: </span><span class="si">{</span><span class="n">weight</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -457,24 +457,24 @@ <h2>Performance Attribution<a class="headerlink" href="#performance-attribution"
 <p>Analyze performance contribution over time:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Calculate performance attribution using openseries</span>
 <span class="c1"># Individual asset performance is available through openseries properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== PERFORMANCE ATTRIBUTION ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== PERFORMANCE ATTRIBUTION ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">series</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">):</span>
     <span class="n">weight</span> <span class="o">=</span> <span class="n">equal_weights</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
     <span class="n">asset_return</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span>
     <span class="n">contribution</span> <span class="o">=</span> <span class="n">weight</span> <span class="o">*</span> <span class="n">asset_return</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Return: </span><span class="si">{</span><span class="n">asset_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Contribution: </span><span class="si">{</span><span class="n">contribution</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Return: </span><span class="si">{</span><span class="n">asset_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Contribution: </span><span class="si">{</span><span class="n">contribution</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Cumulative contribution</span>
 <span class="n">cumulative_contrib</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">weighted_returns</span><span class="p">)</span><span class="o">.</span><span class="n">cumprod</span><span class="p">()</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== PERFORMANCE ATTRIBUTION ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Final cumulative contribution by asset:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== PERFORMANCE ATTRIBUTION ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Final cumulative contribution by asset:"</span><span class="p">)</span>
 <span class="n">final_contrib</span> <span class="o">=</span> <span class="n">cumulative_contrib</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
 <span class="k">for</span> <span class="n">asset</span><span class="p">,</span> <span class="n">contrib</span> <span class="ow">in</span> <span class="n">final_contrib</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">contrib</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">asset</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">contrib</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -490,16 +490,16 @@ <h2>Rolling Portfolio Analysis<a class="headerlink" href="#rolling-portfolio-ana
 <span class="c1"># Calculate rolling correlation</span>
 <span class="n">rolling_corr</span> <span class="o">=</span> <span class="n">portfolio_vs_market</span><span class="o">.</span><span class="n">rolling_corr</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>  <span class="c1"># 1-year rolling</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Rolling correlation calculated for </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">rolling_corr</span><span class="p">)</span><span class="si">}</span><span class="s2"> periods&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Correlation range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Rolling correlation calculated for </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">rolling_corr</span><span class="p">)</span><span class="si">}</span><span class="s2"> periods"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average correlation: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Correlation range: </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_corr</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rolling portfolio volatility</span>
 <span class="n">portfolio_rolling_vol</span> <span class="o">=</span> <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">rolling_vol</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">252</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Rolling volatility statistics:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average volatility: </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility range: </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Rolling volatility statistics:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average volatility: </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility range: </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_rolling_vol</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -508,13 +508,13 @@ <h2>Rebalancing Analysis<a class="headerlink" href="#rebalancing-analysis" title
 <p>Analyze the impact of rebalancing frequency using the realistic <cite>rebalanced_portfolio</cite> method:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Compare different rebalancing frequencies using realistic simulation</span>
 <span class="n">frequencies</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">63</span><span class="p">]</span>  <span class="c1"># Daily, monthly, quarterly</span>
-<span class="n">frequency_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;Daily&quot;</span><span class="p">,</span> <span class="s2">&quot;Monthly&quot;</span><span class="p">,</span> <span class="s2">&quot;Quarterly&quot;</span><span class="p">]</span>
+<span class="n">frequency_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"Daily"</span><span class="p">,</span> <span class="s2">"Monthly"</span><span class="p">,</span> <span class="s2">"Quarterly"</span><span class="p">]</span>
 
 <span class="n">rebalanced_portfolios</span> <span class="o">=</span> <span class="p">[]</span>
 
 <span class="k">for</span> <span class="n">freq</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">frequencies</span><span class="p">,</span> <span class="n">frequency_names</span><span class="p">):</span>
      <span class="n">portfolio</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">rebalanced_portfolio</span><span class="p">(</span>
-          <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> Rebalanced&quot;</span><span class="p">,</span>
+          <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> Rebalanced"</span><span class="p">,</span>
           <span class="n">frequency</span><span class="o">=</span><span class="n">freq</span><span class="p">,</span>
           <span class="n">bal_weights</span><span class="o">=</span><span class="n">equal_weights</span>
      <span class="p">)</span>
@@ -522,7 +522,7 @@ <h2>Rebalancing Analysis<a class="headerlink" href="#rebalancing-analysis" title
 
 <span class="c1"># Compare with theoretical portfolio</span>
 <span class="n">assets</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="n">equal_weights</span>
-<span class="n">theoretical_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Theoretical&quot;</span><span class="p">)</span>
+<span class="n">theoretical_portfolio_df</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Theoretical"</span><span class="p">)</span>
 <span class="n">theoretical_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">theoretical_portfolio_df</span><span class="p">)</span>
 
 <span class="c1"># Create comprehensive comparison</span>
@@ -530,23 +530,23 @@ <h2>Rebalancing Analysis<a class="headerlink" href="#rebalancing-analysis" title
 <span class="n">comparison_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">all_portfolios</span><span class="p">)</span>
 <span class="n">comparison_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== REALISTIC REBALANCING COMPARISON ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Strategy | Return | Volatility | Sharpe | Max DD&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;-&quot;</span> <span class="o">*</span> <span class="mi">50</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== REALISTIC REBALANCING COMPARISON ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Strategy | Return | Volatility | Sharpe | Max DD"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"-"</span> <span class="o">*</span> <span class="mi">50</span><span class="p">)</span>
 
 <span class="k">for</span> <span class="n">series</span> <span class="ow">in</span> <span class="n">all_portfolios</span><span class="p">:</span>
-     <span class="n">ret</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Geometric return&#39;</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
-     <span class="n">vol</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
-     <span class="n">sharpe</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Return vol ratio&#39;</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
-     <span class="n">max_dd</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Max drawdown&#39;</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
+     <span class="n">ret</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Geometric return'</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
+     <span class="n">vol</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
+     <span class="n">sharpe</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Return vol ratio'</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+     <span class="n">max_dd</span> <span class="o">=</span> <span class="n">comparison_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Max drawdown'</span><span class="p">,</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="mi">100</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">:</span><span class="s2">&gt;15</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">ret</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2">% | </span><span class="si">{</span><span class="n">vol</span><span class="si">:</span><span class="s2">10.2f</span><span class="si">}</span><span class="s2">% | </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">max_dd</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2">%&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">:</span><span class="s2">&gt;15</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">ret</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2">% | </span><span class="si">{</span><span class="n">vol</span><span class="si">:</span><span class="s2">10.2f</span><span class="si">}</span><span class="s2">% | </span><span class="si">{</span><span class="n">sharpe</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2"> | </span><span class="si">{</span><span class="n">max_dd</span><span class="si">:</span><span class="s2">6.2f</span><span class="si">}</span><span class="s2">%"</span><span class="p">)</span>
 
 <span class="c1"># Analyze transaction costs</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== TRANSACTION COST ANALYSIS ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== TRANSACTION COST ANALYSIS ==="</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">freq</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">frequencies</span><span class="p">,</span> <span class="n">frequency_names</span><span class="p">):</span>
      <span class="n">detailed_portfolio</span> <span class="o">=</span> <span class="n">assets</span><span class="o">.</span><span class="n">rebalanced_portfolio</span><span class="p">(</span>
-          <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> Detailed&quot;</span><span class="p">,</span>
+          <span class="n">name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2"> Detailed"</span><span class="p">,</span>
           <span class="n">frequency</span><span class="o">=</span><span class="n">freq</span><span class="p">,</span>
           <span class="n">bal_weights</span><span class="o">=</span><span class="n">equal_weights</span><span class="p">,</span>
           <span class="n">drop_extras</span><span class="o">=</span><span class="kc">False</span>  <span class="c1"># Get detailed trading data</span>
@@ -555,12 +555,12 @@ <h2>Rebalancing Analysis<a class="headerlink" href="#rebalancing-analysis" title
      <span class="c1"># Count rebalancing events</span>
      <span class="n">rebalancing_days</span> <span class="o">=</span> <span class="mi">0</span>
      <span class="k">for</span> <span class="n">series</span> <span class="ow">in</span> <span class="n">detailed_portfolio</span><span class="o">.</span><span class="n">constituents</span><span class="p">:</span>
-          <span class="k">if</span> <span class="s2">&quot;buysell_qty&quot;</span> <span class="ow">in</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">:</span>
+          <span class="k">if</span> <span class="s2">"buysell_qty"</span> <span class="ow">in</span> <span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="p">:</span>
                 <span class="c1"># Count days with non-zero trading</span>
                 <span class="n">trading_days</span> <span class="o">=</span> <span class="p">(</span><span class="n">series</span><span class="o">.</span><span class="n">tsdf</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">any</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
                 <span class="n">rebalancing_days</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">rebalancing_days</span><span class="p">,</span> <span class="n">trading_days</span><span class="p">)</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">name</span><span class="si">:</span><span class="s2">&gt;15</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">rebalancing_days</span><span class="si">}</span><span class="s2"> rebalancing events&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">name</span><span class="si">:</span><span class="s2">&gt;15</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">rebalancing_days</span><span class="si">}</span><span class="s2"> rebalancing events"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -575,9 +575,9 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
 <span class="n">worst_days_threshold</span> <span class="o">=</span> <span class="n">market_returns_df</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="mf">0.05</span><span class="p">)</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 <span class="n">worst_days</span> <span class="o">=</span> <span class="n">market_returns_df</span><span class="p">[</span><span class="n">market_returns_df</span> <span class="o">&lt;=</span> <span class="n">worst_days_threshold</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== STRESS TEST RESULTS ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Market stress threshold: </span><span class="si">{</span><span class="n">worst_days_threshold</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of stress days: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">worst_days</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== STRESS TEST RESULTS ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Market stress threshold: </span><span class="si">{</span><span class="n">worst_days_threshold</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of stress days: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">worst_days</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Portfolio performance during stress (modifies original)</span>
 <span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
@@ -587,41 +587,41 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
 <span class="n">stress_dates</span> <span class="o">=</span> <span class="n">worst_days</span><span class="o">.</span><span class="n">index</span>
 <span class="n">portfolio_stress_returns</span> <span class="o">=</span> <span class="n">portfolio_returns_df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">stress_dates</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio average return during stress: </span><span class="si">{</span><span class="n">portfolio_stress_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio worst day during stress: </span><span class="si">{</span><span class="n">portfolio_stress_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio average return during stress: </span><span class="si">{</span><span class="n">portfolio_stress_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio worst day during stress: </span><span class="si">{</span><span class="n">portfolio_stress_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="summary-report">
 <h2>Summary Report<a class="headerlink" href="#summary-report" title="Link to this heading"></a></h2>
 <p>Generate a comprehensive portfolio analysis report:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;PORTFOLIO ANALYSIS SUMMARY REPORT&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Analysis Period: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of Assets: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Asset Universe: </span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">s</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">])</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- EQUAL WEIGHT PORTFOLIO PERFORMANCE ---&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR (daily): </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- PORTFOLIO CHARACTERISTICS ---&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span> <span class="o">+</span> <span class="s2">"="</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"PORTFOLIO ANALYSIS SUMMARY REPORT"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"="</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Analysis Period: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of Assets: </span><span class="si">{</span><span class="n">assets</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Asset Universe: </span><span class="si">{</span><span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">label</span><span class="w"> </span><span class="k">for</span><span class="w"> </span><span class="n">s</span><span class="w"> </span><span class="ow">in</span><span class="w"> </span><span class="n">assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">])</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- EQUAL WEIGHT PORTFOLIO PERFORMANCE ---"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR (daily): </span><span class="si">{</span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- PORTFOLIO CHARACTERISTICS ---"</span><span class="p">)</span>
 <span class="n">avg_correlation</span> <span class="o">=</span> <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average Asset Correlation: </span><span class="si">{</span><span class="n">avg_correlation</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio Diversification Benefit: </span><span class="si">{</span><span class="p">(</span><span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average Asset Correlation: </span><span class="si">{</span><span class="n">avg_correlation</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio Diversification Benefit: </span><span class="si">{</span><span class="p">(</span><span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">equal_weight_portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Export results</span>
-<span class="n">portfolio_metrics</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="s2">&quot;portfolio_analysis.xlsx&quot;</span><span class="p">)</span>
-<span class="n">correlation_matrix</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="s2">&quot;correlation_matrix.xlsx&quot;</span><span class="p">)</span>
+<span class="n">portfolio_metrics</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="s2">"portfolio_analysis.xlsx"</span><span class="p">)</span>
+<span class="n">correlation_matrix</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="s2">"correlation_matrix.xlsx"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Results exported to Excel files&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Analysis complete!&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Results exported to Excel files"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Analysis complete!"</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>This tutorial provides a comprehensive framework for portfolio analysis using openseries. You can extend these techniques for more sophisticated portfolio management strategies.</p>
diff --git a/docs/build/html/tutorials/risk_management.html b/docs/build/html/tutorials/risk_management.html
index 4352bb34..4d977a15 100644
--- a/docs/build/html/tutorials/risk_management.html
+++ b/docs/build/html/tutorials/risk_management.html
@@ -138,31 +138,31 @@ <h2>Setting Up Risk Analysis<a class="headerlink" href="#setting-up-risk-analysi
 <span class="kn">from</span><span class="w"> </span><span class="nn">openseries</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenTimeSeries</span><span class="p">,</span> <span class="n">OpenFrame</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">datetime</span><span class="w"> </span><span class="kn">import</span> <span class="n">datetime</span><span class="p">,</span> <span class="n">timedelta</span>
 <span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
-<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s1">&#39;ignore&#39;</span><span class="p">)</span>
+<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s1">'ignore'</span><span class="p">)</span>
 
 <span class="c1"># Download data for a mixed portfolio</span>
 <span class="n">tickers</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;AAPL&quot;</span><span class="p">:</span> <span class="s2">&quot;Apple Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;GOOGL&quot;</span><span class="p">:</span> <span class="s2">&quot;Alphabet Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;MSFT&quot;</span><span class="p">:</span> <span class="s2">&quot;Microsoft Corp.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;TSLA&quot;</span><span class="p">:</span> <span class="s2">&quot;Tesla Inc.&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;SPY&quot;</span><span class="p">:</span> <span class="s2">&quot;SPDR S&amp;P 500 ETF&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;QQQ&quot;</span><span class="p">:</span> <span class="s2">&quot;Invesco QQQ Trust&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;TLT&quot;</span><span class="p">:</span> <span class="s2">&quot;iShares 20+ Year Treasury&quot;</span><span class="p">,</span>
-     <span class="s2">&quot;GLD&quot;</span><span class="p">:</span> <span class="s2">&quot;SPDR Gold Shares&quot;</span>
+     <span class="s2">"AAPL"</span><span class="p">:</span> <span class="s2">"Apple Inc."</span><span class="p">,</span>
+     <span class="s2">"GOOGL"</span><span class="p">:</span> <span class="s2">"Alphabet Inc."</span><span class="p">,</span>
+     <span class="s2">"MSFT"</span><span class="p">:</span> <span class="s2">"Microsoft Corp."</span><span class="p">,</span>
+     <span class="s2">"TSLA"</span><span class="p">:</span> <span class="s2">"Tesla Inc."</span><span class="p">,</span>
+     <span class="s2">"SPY"</span><span class="p">:</span> <span class="s2">"SPDR S&amp;P 500 ETF"</span><span class="p">,</span>
+     <span class="s2">"QQQ"</span><span class="p">:</span> <span class="s2">"Invesco QQQ Trust"</span><span class="p">,</span>
+     <span class="s2">"TLT"</span><span class="p">:</span> <span class="s2">"iShares 20+ Year Treasury"</span><span class="p">,</span>
+     <span class="s2">"GLD"</span><span class="p">:</span> <span class="s2">"SPDR Gold Shares"</span>
 <span class="p">}</span>
 
 <span class="c1"># Download 3 years of data</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">tickers</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># This may fail if the ticker is invalid or data unavailable</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;3y&quot;</span><span class="p">)</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"3y"</span><span class="p">)</span>
      <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">]</span>
      <span class="p">)</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
 
 <span class="c1"># Create portfolio frame</span>
 <span class="n">portfolio_assets</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">series_list</span><span class="p">)</span>
@@ -172,75 +172,75 @@ <h2>Setting Up Risk Analysis<a class="headerlink" href="#setting-up-risk-analysi
 
 <span class="c1"># Set weights on the frame first</span>
 <span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Diversified Portfolio&quot;</span><span class="p">,</span>
-     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Diversified Portfolio"</span><span class="p">,</span>
+     <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span>
 <span class="p">)</span>
 <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Portfolio created with </span><span class="si">{</span><span class="n">n_assets</span><span class="si">}</span><span class="s2"> assets&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Date range: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Portfolio created with </span><span class="si">{</span><span class="n">n_assets</span><span class="si">}</span><span class="s2"> assets"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="basic-risk-metrics">
 <h2>Basic Risk Metrics<a class="headerlink" href="#basic-risk-metrics" title="Link to this heading"></a></h2>
 <p>Start with fundamental risk measurements:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=== BASIC RISK METRICS ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"=== BASIC RISK METRICS ==="</span><span class="p">)</span>
 
 <span class="c1"># Volatility measures</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Downside Deviation: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">downside_deviation</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Downside Deviation: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">downside_deviation</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Return distribution</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Skewness: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kurtosis: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Skewness: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kurtosis: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Tail risk</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Single Day: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">worst</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Month: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">worst_month</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Single Day: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">worst</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Month: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">worst_month</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Drawdown analysis</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Max Drawdown Date: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown_date</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Max Drawdown Date: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown_date</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="value-at-risk-var-analysis">
 <h2>Value at Risk (VaR) Analysis<a class="headerlink" href="#value-at-risk-var-analysis" title="Link to this heading"></a></h2>
 <p>Calculate VaR at different confidence levels:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== VALUE AT RISK ANALYSIS ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== VALUE AT RISK ANALYSIS ==="</span><span class="p">)</span>
 
 <span class="c1"># VaR at different confidence levels</span>
 <span class="n">confidence_levels</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.90</span><span class="p">,</span> <span class="mf">0.95</span><span class="p">,</span> <span class="mf">0.99</span><span class="p">]</span>
 
 <span class="k">for</span> <span class="n">level</span> <span class="ow">in</span> <span class="n">confidence_levels</span><span class="p">:</span>
      <span class="n">var_value</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">var_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="n">level</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">level</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2">% VaR (daily): </span><span class="si">{</span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">level</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2">% VaR (daily): </span><span class="si">{</span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Convert daily VaR to different time horizons</span>
 <span class="c1"># Assuming normal distribution and independence</span>
 <span class="n">daily_var_95</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">var_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="mf">0.95</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== VaR TIME HORIZONS (95% confidence) ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;1-day VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== VaR TIME HORIZONS (95% confidence) ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"1-day VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="c1"># Scale VaR to different time horizons</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;1-week VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">5</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;1-month VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">22</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;1-year VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">252</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"1-week VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">5</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"1-month VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">22</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"1-year VaR: </span><span class="si">{</span><span class="n">daily_var_95</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="mi">252</span><span class="w"> </span><span class="o">**</span><span class="w"> </span><span class="mf">0.5</span><span class="p">)</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="conditional-value-at-risk-cvar">
 <h2>Conditional Value at Risk (CVaR)<a class="headerlink" href="#conditional-value-at-risk-cvar" title="Link to this heading"></a></h2>
 <p>Analyze expected shortfall beyond VaR:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== CONDITIONAL VALUE AT RISK (CVaR) ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== CONDITIONAL VALUE AT RISK (CVaR) ==="</span><span class="p">)</span>
 
 <span class="k">for</span> <span class="n">level</span> <span class="ow">in</span> <span class="n">confidence_levels</span><span class="p">:</span>
      <span class="n">cvar_value</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">cvar_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="n">level</span><span class="p">)</span>
      <span class="n">var_value</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">var_down_func</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="n">level</span><span class="p">)</span>
 
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">level</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2">% CVaR: </span><span class="si">{</span><span class="n">cvar_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> (VaR: </span><span class="si">{</span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">)&quot;</span><span class="p">)</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Expected loss beyond VaR: </span><span class="si">{</span><span class="n">cvar_value</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">level</span><span class="o">*</span><span class="mi">100</span><span class="si">:</span><span class="s2">.0f</span><span class="si">}</span><span class="s2">% CVaR: </span><span class="si">{</span><span class="n">cvar_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> (VaR: </span><span class="si">{</span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">)"</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Expected loss beyond VaR: </span><span class="si">{</span><span class="n">cvar_value</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">var_value</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -250,23 +250,23 @@ <h2>Rolling Risk Analysis<a class="headerlink" href="#rolling-risk-analysis" tit
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Calculate rolling risk metrics</span>
 <span class="n">window</span> <span class="o">=</span> <span class="mi">252</span>  <span class="c1"># 1-year rolling window</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== ROLLING RISK ANALYSIS (</span><span class="si">{</span><span class="n">window</span><span class="si">}</span><span class="s2">-day window) ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== ROLLING RISK ANALYSIS (</span><span class="si">{</span><span class="n">window</span><span class="si">}</span><span class="s2">-day window) ==="</span><span class="p">)</span>
 
 <span class="c1"># Rolling volatility</span>
 <span class="n">rolling_vol</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">rolling_vol</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="n">window</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling Volatility - Current: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling Volatility - Average: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling Volatility - Range: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling Volatility - Current: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling Volatility - Average: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling Volatility - Range: </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">rolling_vol</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rolling VaR</span>
 <span class="n">rolling_var</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">rolling_var_down</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="n">window</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling VaR (95%) - Current: </span><span class="si">{</span><span class="n">rolling_var</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling VaR (95%) - Average: </span><span class="si">{</span><span class="n">rolling_var</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling VaR (95%) - Current: </span><span class="si">{</span><span class="n">rolling_var</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling VaR (95%) - Average: </span><span class="si">{</span><span class="n">rolling_var</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Rolling CVaR</span>
 <span class="n">rolling_cvar</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">rolling_cvar_down</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="n">window</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling CVaR (95%) - Current: </span><span class="si">{</span><span class="n">rolling_cvar</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Rolling CVaR (95%) - Average: </span><span class="si">{</span><span class="n">rolling_cvar</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling CVaR (95%) - Current: </span><span class="si">{</span><span class="n">rolling_cvar</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Rolling CVaR (95%) - Average: </span><span class="si">{</span><span class="n">rolling_cvar</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -275,7 +275,7 @@ <h2>Stress Testing<a class="headerlink" href="#stress-testing" title="Link to th
 <p>Test portfolio performance under extreme scenarios:</p>
 <section id="historical-stress-testing">
 <h3>Historical Stress Testing<a class="headerlink" href="#historical-stress-testing" title="Link to this heading"></a></h3>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== HISTORICAL STRESS TESTING ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== HISTORICAL STRESS TESTING ==="</span><span class="p">)</span>
 
 <span class="c1"># Convert to returns for analysis (modifies original)</span>
 <span class="n">portfolio</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
@@ -289,42 +289,42 @@ <h3>Historical Stress Testing<a class="headerlink" href="#historical-stress-test
 <span class="n">worst_1_percent</span> <span class="o">=</span> <span class="n">returns_data</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="mf">0.01</span><span class="p">)</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 <span class="n">worst_5_percent</span> <span class="o">=</span> <span class="n">returns_data</span><span class="o">.</span><span class="n">quantile</span><span class="p">(</span><span class="mf">0.05</span><span class="p">)</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst 1% threshold: </span><span class="si">{</span><span class="n">worst_1_percent</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst 5% threshold: </span><span class="si">{</span><span class="n">worst_5_percent</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst 1% threshold: </span><span class="si">{</span><span class="n">worst_1_percent</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst 5% threshold: </span><span class="si">{</span><span class="n">worst_5_percent</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Count extreme events</span>
 <span class="n">extreme_events_1pct</span> <span class="o">=</span> <span class="p">(</span><span class="n">returns_data</span> <span class="o">&lt;=</span> <span class="n">worst_1_percent</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 <span class="n">extreme_events_5pct</span> <span class="o">=</span> <span class="p">(</span><span class="n">returns_data</span> <span class="o">&lt;=</span> <span class="n">worst_5_percent</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Days with returns &lt;= 1% threshold: </span><span class="si">{</span><span class="n">extreme_events_1pct</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Days with returns &lt;= 5% threshold: </span><span class="si">{</span><span class="n">extreme_events_5pct</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Days with returns &lt;= 1% threshold: </span><span class="si">{</span><span class="n">extreme_events_1pct</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Days with returns &lt;= 5% threshold: </span><span class="si">{</span><span class="n">extreme_events_5pct</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Worst consecutive days - simplified approach</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Worst 5 single days:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Worst 5 single days:"</span><span class="p">)</span>
 <span class="n">returns_series</span> <span class="o">=</span> <span class="n">returns_data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>  <span class="c1"># Get the first (and only) column</span>
 <span class="n">worst_5_days</span> <span class="o">=</span> <span class="n">returns_series</span><span class="o">.</span><span class="n">nsmallest</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">date</span><span class="p">,</span> <span class="n">return_val</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">worst_5_days</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">date</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%Y-%m-</span><span class="si">%d</span><span class="s1">&#39;</span><span class="p">)</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">return_val</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">. </span><span class="si">{</span><span class="n">date</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">'%Y-%m-</span><span class="si">%d</span><span class="s1">'</span><span class="p">)</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">return_val</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="scenario-analysis">
 <h3>Scenario Analysis<a class="headerlink" href="#scenario-analysis" title="Link to this heading"></a></h3>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== SCENARIO ANALYSIS ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== SCENARIO ANALYSIS ==="</span><span class="p">)</span>
 
 <span class="c1"># Define stress scenarios (percentage moves in underlying assets)</span>
 <span class="n">scenarios</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s2">&quot;Market Crash&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.20</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.25</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.22</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.30</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.18</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.20</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.10</span><span class="p">],</span>
-     <span class="s2">&quot;Tech Selloff&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.35</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.40</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.30</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.45</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.03</span><span class="p">],</span>
-     <span class="s2">&quot;Interest Rate Shock&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.12</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.05</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.01</span><span class="p">],</span>
-     <span class="s2">&quot;Flight to Quality&quot;</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="mf">0.10</span><span class="p">,</span> <span class="mf">0.12</span><span class="p">,</span> <span class="mf">0.20</span><span class="p">,</span> <span class="mf">0.15</span><span class="p">]</span>
+     <span class="s2">"Market Crash"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.20</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.25</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.22</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.30</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.18</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.20</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.10</span><span class="p">],</span>
+     <span class="s2">"Tech Selloff"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.35</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.40</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.30</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.45</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.03</span><span class="p">],</span>
+     <span class="s2">"Interest Rate Shock"</span><span class="p">:</span> <span class="p">[</span><span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.12</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.05</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.01</span><span class="p">],</span>
+     <span class="s2">"Flight to Quality"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">,</span> <span class="mf">0.08</span><span class="p">,</span> <span class="o">-</span><span class="mf">0.10</span><span class="p">,</span> <span class="mf">0.10</span><span class="p">,</span> <span class="mf">0.12</span><span class="p">,</span> <span class="mf">0.20</span><span class="p">,</span> <span class="mf">0.15</span><span class="p">]</span>
 <span class="p">}</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Portfolio impact under stress scenarios:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Portfolio impact under stress scenarios:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">scenario_name</span><span class="p">,</span> <span class="n">asset_moves</span> <span class="ow">in</span> <span class="n">scenarios</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
      <span class="c1"># Calculate portfolio impact</span>
      <span class="n">portfolio_impact</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">w</span> <span class="o">*</span> <span class="n">move</span> <span class="k">for</span> <span class="n">w</span><span class="p">,</span> <span class="n">move</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">equal_weights</span><span class="p">,</span> <span class="n">asset_moves</span><span class="p">))</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  </span><span class="si">{</span><span class="n">scenario_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">portfolio_impact</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  </span><span class="si">{</span><span class="n">scenario_name</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">portfolio_impact</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -332,7 +332,7 @@ <h3>Scenario Analysis<a class="headerlink" href="#scenario-analysis" title="Link
 <section id="monte-carlo-risk-simulation">
 <h2>Monte Carlo Risk Simulation<a class="headerlink" href="#monte-carlo-risk-simulation" title="Link to this heading"></a></h2>
 <p>Use Monte Carlo methods for risk assessment:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== MONTE CARLO RISK SIMULATION ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== MONTE CARLO RISK SIMULATION ==="</span><span class="p">)</span>
 
 <span class="c1"># Import the simulate_portfolios function</span>
 <span class="kn">from</span><span class="w"> </span><span class="nn">openseries.portfoliotools</span><span class="w"> </span><span class="kn">import</span> <span class="n">simulate_portfolios</span>
@@ -349,9 +349,9 @@ <h2>Monte Carlo Risk Simulation<a class="headerlink" href="#monte-carlo-risk-sim
 <span class="p">)</span>
 
 <span class="c1"># Extract portfolio metrics from simulation</span>
-<span class="n">portfolio_returns</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">&#39;ret&#39;</span><span class="p">]</span>
-<span class="n">portfolio_volatilities</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">&#39;stdev&#39;</span><span class="p">]</span>
-<span class="n">portfolio_sharpes</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span>
+<span class="n">portfolio_returns</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">'ret'</span><span class="p">]</span>
+<span class="n">portfolio_volatilities</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">'stdev'</span><span class="p">]</span>
+<span class="n">portfolio_sharpes</span> <span class="o">=</span> <span class="n">simulated_portfolios</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span>
 
 <span class="c1"># Calculate risk metrics from simulation</span>
 <span class="c1"># Calculate 5th percentile manually</span>
@@ -360,34 +360,34 @@ <h2>Monte Carlo Risk Simulation<a class="headerlink" href="#monte-carlo-risk-sim
 <span class="n">sim_var_95</span> <span class="o">=</span> <span class="n">sorted_returns</span><span class="p">[</span><span class="n">percentile_idx</span><span class="p">]</span>
 <span class="n">sim_cvar_95</span> <span class="o">=</span> <span class="n">portfolio_returns</span><span class="p">[</span><span class="n">portfolio_returns</span> <span class="o">&lt;=</span> <span class="n">sim_var_95</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monte Carlo Results (</span><span class="si">{</span><span class="n">num_simulations</span><span class="si">:</span><span class="s2">,</span><span class="si">}</span><span class="s2"> simulations):&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Expected Return: </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average Volatility: </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR: </span><span class="si">{</span><span class="n">sim_var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR: </span><span class="si">{</span><span class="n">sim_cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monte Carlo Results (</span><span class="si">{</span><span class="n">num_simulations</span><span class="si">:</span><span class="s2">,</span><span class="si">}</span><span class="s2"> simulations):"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Expected Return: </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average Volatility: </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR: </span><span class="si">{</span><span class="n">sim_var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR: </span><span class="si">{</span><span class="n">sim_cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="c1"># Calculate percentiles manually</span>
 <span class="n">worst_idx</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sorted_returns</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.001</span><span class="p">)</span>
 <span class="n">best_idx</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sorted_returns</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.999</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Worst Case (0.1%): </span><span class="si">{</span><span class="n">sorted_returns</span><span class="p">[</span><span class="n">worst_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Best Case (99.9%): </span><span class="si">{</span><span class="n">sorted_returns</span><span class="p">[</span><span class="n">best_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Average Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Worst Case (0.1%): </span><span class="si">{</span><span class="n">sorted_returns</span><span class="p">[</span><span class="n">worst_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Best Case (99.9%): </span><span class="si">{</span><span class="n">sorted_returns</span><span class="p">[</span><span class="n">best_idx</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Average Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Show distribution of portfolio characteristics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Portfolio Distribution:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Return Range: </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility Range: </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Range: </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Portfolio Distribution:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Return Range: </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_returns</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility Range: </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_volatilities</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Range: </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">portfolio_sharpes</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="risk-decomposition">
 <h2>Risk Decomposition<a class="headerlink" href="#risk-decomposition" title="Link to this heading"></a></h2>
 <p>Analyze risk contribution by asset:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK DECOMPOSITION ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK DECOMPOSITION ==="</span><span class="p">)</span>
 
 <span class="c1"># Calculate individual asset volatilities using OpenFrame</span>
 <span class="n">asset_metrics</span> <span class="o">=</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
-<span class="n">asset_vols</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">&#39;Volatility&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
+<span class="n">asset_vols</span> <span class="o">=</span> <span class="n">asset_metrics</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s1">'Volatility'</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
 
 <span class="c1"># Portfolio volatility</span>
 <span class="n">portfolio_vol</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span>
@@ -397,50 +397,50 @@ <h2>Risk Decomposition<a class="headerlink" href="#risk-decomposition" title="Li
 
 <span class="c1"># Risk contribution analysis using openseries</span>
 <span class="c1"># Create portfolio to get portfolio-level metrics</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Portfolio&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Portfolio"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 <span class="n">portfolio_vol</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Risk Contribution Analysis:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Risk Contribution Analysis:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">series</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">portfolio_assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">):</span>
     <span class="n">weight</span> <span class="o">=</span> <span class="n">equal_weights</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
     <span class="n">asset_vol</span> <span class="o">=</span> <span class="n">asset_vols</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Individual Volatility: </span><span class="si">{</span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Weighted Volatility Contribution: </span><span class="si">{</span><span class="n">weight</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weight: </span><span class="si">{</span><span class="n">weight</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Individual Volatility: </span><span class="si">{</span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Weighted Volatility Contribution: </span><span class="si">{</span><span class="n">weight</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">asset_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Verify portfolio metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Verification:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio volatility: </span><span class="si">{</span><span class="n">portfolio_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Verification:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio volatility: </span><span class="si">{</span><span class="n">portfolio_vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="risk-adjusted-performance">
 <h2>Risk-Adjusted Performance<a class="headerlink" href="#risk-adjusted-performance" title="Link to this heading"></a></h2>
 <p>Evaluate risk-adjusted returns:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK-ADJUSTED PERFORMANCE ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK-ADJUSTED PERFORMANCE ==="</span><span class="p">)</span>
 
 <span class="c1"># Sharpe ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Sortino ratio (downside risk only)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Kappa-3 ratio (higher-order downside risk)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kappa-3 Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kappa3_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kappa-3 Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kappa3_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Omega ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Omega Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">omega_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Omega Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">omega_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Compare with individual assets</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK-ADJUSTED COMPARISON ===&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK-ADJUSTED COMPARISON ==="</span><span class="p">)</span>
 <span class="n">all_assets</span> <span class="o">=</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">constituents</span> <span class="o">+</span> <span class="p">[</span><span class="n">portfolio</span><span class="p">]</span>
 <span class="n">comparison_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="n">all_assets</span><span class="p">)</span>
 
 <span class="n">risk_adj_metrics</span> <span class="o">=</span> <span class="n">comparison_frame</span><span class="o">.</span><span class="n">all_properties</span><span class="p">(</span>
-     <span class="n">properties</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;ret_vol_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;sortino_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;kappa3_ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;omega_ratio&#39;</span><span class="p">]</span>
+     <span class="n">properties</span><span class="o">=</span><span class="p">[</span><span class="s1">'ret_vol_ratio'</span><span class="p">,</span> <span class="s1">'sortino_ratio'</span><span class="p">,</span> <span class="s1">'kappa3_ratio'</span><span class="p">,</span> <span class="s1">'omega_ratio'</span><span class="p">]</span>
 <span class="p">)</span>
 
 <span class="nb">print</span><span class="p">(</span><span class="n">risk_adj_metrics</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
@@ -450,134 +450,134 @@ <h2>Risk-Adjusted Performance<a class="headerlink" href="#risk-adjusted-performa
 <section id="risk-monitoring-dashboard">
 <h2>Risk Monitoring Dashboard<a class="headerlink" href="#risk-monitoring-dashboard" title="Link to this heading"></a></h2>
 <p>Create a comprehensive risk monitoring summary using openseries properties and methods:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;RISK MONITORING DASHBOARD&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span> <span class="o">+</span> <span class="s2">"="</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"RISK MONITORING DASHBOARD"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"="</span><span class="o">*</span><span class="mi">60</span><span class="p">)</span>
 
 <span class="c1"># Current date and lookback period</span>
 <span class="n">current_date</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">last_idx</span>
 <span class="n">lookback_date</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">first_idx</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Portfolio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Current Date: </span><span class="si">{</span><span class="n">current_date</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Analysis Period: </span><span class="si">{</span><span class="n">lookback_date</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">current_date</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Observations: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Portfolio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Current Date: </span><span class="si">{</span><span class="n">current_date</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Analysis Period: </span><span class="si">{</span><span class="n">lookback_date</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">current_date</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Observations: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Risk metrics using openseries properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- CURRENT RISK METRICS ---&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Volatility (annualized): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Downside Deviation: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">downside_deviation</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR (daily): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR (daily): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- CURRENT RISK METRICS ---"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Volatility (annualized): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Downside Deviation: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">downside_deviation</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR (daily): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR (daily): </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Performance metrics using openseries properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- PERFORMANCE METRICS ---&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- PERFORMANCE METRICS ---"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Distribution characteristics using openseries properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- RETURN DISTRIBUTION ---&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Skewness: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kurtosis: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Positive Days: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- RETURN DISTRIBUTION ---"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Skewness: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kurtosis: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Positive Days: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Recent performance using openseries properties</span>
 <span class="n">recent_return</span> <span class="o">=</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">z_score</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- RECENT ACTIVITY ---&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Last Return Z-Score: </span><span class="si">{</span><span class="n">recent_return</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- RECENT ACTIVITY ---"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Last Return Z-Score: </span><span class="si">{</span><span class="n">recent_return</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">recent_return</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">2</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  ⚠️  ALERT: Recent return is unusual (|z| &gt; 2)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  ⚠️  ALERT: Recent return is unusual (|z| &gt; 2)"</span><span class="p">)</span>
 <span class="k">elif</span> <span class="nb">abs</span><span class="p">(</span><span class="n">recent_return</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  🚨 WARNING: Recent return is extreme (|z| &gt; 3)&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  🚨 WARNING: Recent return is extreme (|z| &gt; 3)"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  ✅ Recent return is within normal range&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  ✅ Recent return is within normal range"</span><span class="p">)</span>
 
 <span class="c1"># Risk alerts based on openseries metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">--- RISK ALERTS ---&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">--- RISK ALERTS ---"</span><span class="p">)</span>
 <span class="n">alerts</span> <span class="o">=</span> <span class="p">[]</span>
 
 <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span> <span class="o">&gt;</span> <span class="mf">0.25</span><span class="p">:</span>
-     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;High volatility (&gt;25%)&quot;</span><span class="p">)</span>
+     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">"High volatility (&gt;25%)"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mf">0.20</span><span class="p">:</span>
-     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;Large maximum drawdown (&gt;20%)&quot;</span><span class="p">)</span>
+     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">"Large maximum drawdown (&gt;20%)"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span> <span class="o">&lt;</span> <span class="mf">0.5</span><span class="p">:</span>
-     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;Low Sharpe ratio (&lt;0.5)&quot;</span><span class="p">)</span>
+     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">"Low Sharpe ratio (&lt;0.5)"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span> <span class="o">&lt;</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
-     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;Highly negative skew (&lt;-1)&quot;</span><span class="p">)</span>
+     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">"Highly negative skew (&lt;-1)"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span> <span class="o">&gt;</span> <span class="mi">5</span><span class="p">:</span>
-     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;High kurtosis (&gt;5) - fat tails&quot;</span><span class="p">)</span>
+     <span class="n">alerts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">"High kurtosis (&gt;5) - fat tails"</span><span class="p">)</span>
 
 <span class="k">if</span> <span class="n">alerts</span><span class="p">:</span>
      <span class="k">for</span> <span class="n">alert</span> <span class="ow">in</span> <span class="n">alerts</span><span class="p">:</span>
-          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  ⚠️  </span><span class="si">{</span><span class="n">alert</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+          <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  ⚠️  </span><span class="si">{</span><span class="n">alert</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;  ✅ No risk alerts&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="s2">"  ✅ No risk alerts"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="risk-limits-and-controls">
 <h2>Risk Limits and Controls<a class="headerlink" href="#risk-limits-and-controls" title="Link to this heading"></a></h2>
 <p>Implement risk limit monitoring:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK LIMITS MONITORING ===&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK LIMITS MONITORING ==="</span><span class="p">)</span>
 
 <span class="c1"># Define risk limits</span>
 <span class="n">risk_limits</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;max_volatility&#39;</span><span class="p">:</span> <span class="mf">0.20</span><span class="p">,</span>      <span class="c1"># 20% annual volatility</span>
-     <span class="s1">&#39;max_var_daily&#39;</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.03</span><span class="p">,</span>      <span class="c1"># 3% daily VaR</span>
-     <span class="s1">&#39;max_drawdown&#39;</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span>       <span class="c1"># 15% maximum drawdown</span>
-     <span class="s1">&#39;min_sharpe&#39;</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span>           <span class="c1"># Minimum Sharpe ratio</span>
-     <span class="s1">&#39;max_concentration&#39;</span><span class="p">:</span> <span class="mf">0.30</span>    <span class="c1"># Maximum single asset weight</span>
+     <span class="s1">'max_volatility'</span><span class="p">:</span> <span class="mf">0.20</span><span class="p">,</span>      <span class="c1"># 20% annual volatility</span>
+     <span class="s1">'max_var_daily'</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.03</span><span class="p">,</span>      <span class="c1"># 3% daily VaR</span>
+     <span class="s1">'max_drawdown'</span><span class="p">:</span> <span class="o">-</span><span class="mf">0.15</span><span class="p">,</span>       <span class="c1"># 15% maximum drawdown</span>
+     <span class="s1">'min_sharpe'</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span>           <span class="c1"># Minimum Sharpe ratio</span>
+     <span class="s1">'max_concentration'</span><span class="p">:</span> <span class="mf">0.30</span>    <span class="c1"># Maximum single asset weight</span>
 <span class="p">}</span>
 
 <span class="c1"># Check current metrics against limits</span>
 <span class="n">current_metrics</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;volatility&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
-     <span class="s1">&#39;var_daily&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="p">,</span>
-     <span class="s1">&#39;drawdown&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">,</span>
-     <span class="s1">&#39;sharpe&#39;</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
-     <span class="s1">&#39;max_weight&#39;</span><span class="p">:</span> <span class="nb">max</span><span class="p">(</span><span class="n">equal_weights</span><span class="p">)</span>
+     <span class="s1">'volatility'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="p">,</span>
+     <span class="s1">'var_daily'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="p">,</span>
+     <span class="s1">'drawdown'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="p">,</span>
+     <span class="s1">'sharpe'</span><span class="p">:</span> <span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="p">,</span>
+     <span class="s1">'max_weight'</span><span class="p">:</span> <span class="nb">max</span><span class="p">(</span><span class="n">equal_weights</span><span class="p">)</span>
 <span class="p">}</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Risk Limit Monitoring:&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;-&quot;</span> <span class="o">*</span> <span class="mi">40</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Risk Limit Monitoring:"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"-"</span> <span class="o">*</span> <span class="mi">40</span><span class="p">)</span>
 
 <span class="c1"># Volatility check</span>
-<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;volatility&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_volatility&#39;</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;❌ BREACH: Volatility </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;volatility&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_volatility&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">'volatility'</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_volatility'</span><span class="p">]:</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"❌ BREACH: Volatility </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'volatility'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_volatility'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;✅ OK: Volatility </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;volatility&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_volatility&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"✅ OK: Volatility </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'volatility'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_volatility'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># VaR check</span>
-<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;var_daily&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_var_daily&#39;</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;❌ BREACH: VaR </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;var_daily&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_var_daily&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">'var_daily'</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_var_daily'</span><span class="p">]:</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"❌ BREACH: VaR </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'var_daily'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_var_daily'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;✅ OK: VaR </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;var_daily&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_var_daily&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"✅ OK: VaR </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'var_daily'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_var_daily'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Drawdown check</span>
-<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;drawdown&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_drawdown&#39;</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;❌ BREACH: Drawdown </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;drawdown&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_drawdown&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">'drawdown'</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_drawdown'</span><span class="p">]:</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"❌ BREACH: Drawdown </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'drawdown'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_drawdown'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;✅ OK: Drawdown </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;drawdown&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_drawdown&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"✅ OK: Drawdown </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'drawdown'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_drawdown'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Sharpe ratio check</span>
-<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;min_sharpe&#39;</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;❌ BREACH: Sharpe </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;min_sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">'min_sharpe'</span><span class="p">]:</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"❌ BREACH: Sharpe </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> &lt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'min_sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;✅ OK: Sharpe </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;min_sharpe&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"✅ OK: Sharpe </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> &gt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'min_sharpe'</span><span class="p">]</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Concentration check</span>
-<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;max_weight&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_concentration&#39;</span><span class="p">]:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;❌ BREACH: Max weight </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;max_weight&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_concentration&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="k">if</span> <span class="n">current_metrics</span><span class="p">[</span><span class="s1">'max_weight'</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_concentration'</span><span class="p">]:</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"❌ BREACH: Max weight </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'max_weight'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &gt; </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_concentration'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 <span class="k">else</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;✅ OK: Max weight </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">&#39;max_weight&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">&#39;max_concentration&#39;</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"✅ OK: Max weight </span><span class="si">{</span><span class="n">current_metrics</span><span class="p">[</span><span class="s1">'max_weight'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2"> &lt;= </span><span class="si">{</span><span class="n">risk_limits</span><span class="p">[</span><span class="s1">'max_concentration'</span><span class="p">]</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -586,53 +586,53 @@ <h2>Export Risk Report<a class="headerlink" href="#export-risk-report" title="Li
 <p>Save comprehensive risk analysis:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Create comprehensive risk report</span>
 <span class="c1"># Create risk report using openseries methods</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">=== RISK REPORT ===&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Risk metrics are available through openseries properties:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">=== RISK REPORT ==="</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Risk metrics are available through openseries properties:"</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">series</span> <span class="ow">in</span> <span class="n">portfolio_assets</span><span class="o">.</span><span class="n">constituents</span><span class="p">:</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  VaR (95%): </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  CVaR (95%): </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;  Max Drawdown: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">:"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  VaR (95%): </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  CVaR (95%): </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Volatility: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"  Max Drawdown: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.4f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Note: For comprehensive Excel export, use openseries to_xlsx() method</span>
-<span class="n">portfolio_assets</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">&#39;risk_analysis_report.xlsx&#39;</span><span class="p">)</span>
+<span class="n">portfolio_assets</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s1">'risk_analysis_report.xlsx'</span><span class="p">)</span>
 
 <span class="c1"># Alternative: risk_report = pd.DataFrame({</span>
-     <span class="s1">&#39;Metric&#39;</span><span class="p">:</span> <span class="p">[</span>
-          <span class="s1">&#39;Annualized Return&#39;</span><span class="p">,</span> <span class="s1">&#39;Annualized Volatility&#39;</span><span class="p">,</span> <span class="s1">&#39;Sharpe Ratio&#39;</span><span class="p">,</span>
-          <span class="s1">&#39;Sortino Ratio&#39;</span><span class="p">,</span> <span class="s1">&#39;Maximum Drawdown&#39;</span><span class="p">,</span> <span class="s1">&#39;95% VaR (daily)&#39;</span><span class="p">,</span>
-          <span class="s1">&#39;95% CVaR (daily)&#39;</span><span class="p">,</span> <span class="s1">&#39;Skewness&#39;</span><span class="p">,</span> <span class="s1">&#39;Kurtosis&#39;</span><span class="p">,</span> <span class="s1">&#39;Positive Days %&#39;</span>
+     <span class="s1">'Metric'</span><span class="p">:</span> <span class="p">[</span>
+          <span class="s1">'Annualized Return'</span><span class="p">,</span> <span class="s1">'Annualized Volatility'</span><span class="p">,</span> <span class="s1">'Sharpe Ratio'</span><span class="p">,</span>
+          <span class="s1">'Sortino Ratio'</span><span class="p">,</span> <span class="s1">'Maximum Drawdown'</span><span class="p">,</span> <span class="s1">'95% VaR (daily)'</span><span class="p">,</span>
+          <span class="s1">'95% CVaR (daily)'</span><span class="p">,</span> <span class="s1">'Skewness'</span><span class="p">,</span> <span class="s1">'Kurtosis'</span><span class="p">,</span> <span class="s1">'Positive Days %'</span>
      <span class="p">],</span>
-     <span class="s1">&#39;Value&#39;</span><span class="p">:</span> <span class="p">[</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span>
-          <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span>
+     <span class="s1">'Value'</span><span class="p">:</span> <span class="p">[</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
+          <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span>
      <span class="p">]</span>
 <span class="p">})</span>
 
 <span class="c1"># Export to Excel</span>
 <span class="c1"># Export using openseries native method (commented out ExcelWriter approach)</span>
-<span class="c1"># with pd.ExcelWriter(&#39;risk_analysis_report.xlsx&#39;) as writer:</span>
-     <span class="n">risk_report</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Risk Metrics&#39;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
-     <span class="n">risk_decomp</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Risk Decomposition&#39;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
-     <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Correlations&#39;</span><span class="p">)</span>
+<span class="c1"># with pd.ExcelWriter('risk_analysis_report.xlsx') as writer:</span>
+     <span class="n">risk_report</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">'Risk Metrics'</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+     <span class="n">risk_decomp</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">'Risk Decomposition'</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+     <span class="n">correlation_matrix</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">'Correlations'</span><span class="p">)</span>
 
      <span class="c1"># Add rolling metrics if available</span>
-     <span class="k">if</span> <span class="s1">&#39;rolling_vol&#39;</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
-          <span class="n">rolling_vol</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Rolling Volatility&#39;</span><span class="p">)</span>
-     <span class="k">if</span> <span class="s1">&#39;rolling_var&#39;</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
-          <span class="n">rolling_var</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Rolling VaR&#39;</span><span class="p">)</span>
+     <span class="k">if</span> <span class="s1">'rolling_vol'</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
+          <span class="n">rolling_vol</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">'Rolling Volatility'</span><span class="p">)</span>
+     <span class="k">if</span> <span class="s1">'rolling_var'</span> <span class="ow">in</span> <span class="nb">locals</span><span class="p">():</span>
+          <span class="n">rolling_var</span><span class="o">.</span><span class="n">to_excel</span><span class="p">(</span><span class="n">writer</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">'Rolling VaR'</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Risk analysis report exported to &#39;risk_analysis_report.xlsx&#39;&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Risk management analysis complete!&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Risk analysis report exported to 'risk_analysis_report.xlsx'"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Risk management analysis complete!"</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>This comprehensive risk management tutorial provides the foundation for implementing robust risk controls and monitoring systems using openseries.</p>
diff --git a/docs/build/html/user_guide/core_concepts.html b/docs/build/html/user_guide/core_concepts.html
index bc4aa1bc..3f8d87dc 100644
--- a/docs/build/html/user_guide/core_concepts.html
+++ b/docs/build/html/user_guide/core_concepts.html
@@ -203,16 +203,16 @@ <h3>Core Properties<a class="headerlink" href="#core-properties" title="Link to
 <span class="p">)</span>
 
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Sample Asset&quot;</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Sample Asset"</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
      <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
 <span class="p">)</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>  <span class="c1"># Convert returns to cumulative prices</span>
 
 <span class="c1"># Core properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Name: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;First date: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Last date: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Value type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Name: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"First date: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Last date: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Value type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -228,7 +228,7 @@ <h3>Data Immutability<a class="headerlink" href="#data-immutability" title="Link
 
 <span class="c1"># Transformations modify the original object (method chaining)</span>
 <span class="n">series</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>    <span class="c1"># Modifies original series</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>  <span class="c1"># Usually length - 1</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>  <span class="c1"># Usually length - 1</span>
 </pre></div>
 </div>
 </section>
@@ -238,16 +238,16 @@ <h3>Value Types<a class="headerlink" href="#value-types" title="Link to this hea
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">openseries</span><span class="w"> </span><span class="kn">import</span> <span class="n">ValueType</span>
 
 <span class="c1"># Common value types</span>
-<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">)</span>      <span class="c1"># &quot;Price(Close)&quot;</span>
-<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">)</span>       <span class="c1"># &quot;Return(Total)&quot;</span>
-<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">ROLLVOL</span><span class="p">)</span>    <span class="c1"># &quot;Rolling volatility&quot;</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">PRICE</span><span class="p">)</span>      <span class="c1"># "Price(Close)"</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">)</span>       <span class="c1"># "Return(Total)"</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">ValueType</span><span class="o">.</span><span class="n">ROLLVOL</span><span class="p">)</span>    <span class="c1"># "Rolling volatility"</span>
 
 <span class="c1"># Check series type</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Series type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Series type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Type changes with transformations</span>
 <span class="n">series</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>  <span class="c1"># Modifies original</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Returns type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Returns type: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">valuetype</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -273,7 +273,7 @@ <h3>Managing Multiple Series<a class="headerlink" href="#managing-multiple-serie
 <span class="n">frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span>
      <span class="n">constituents</span><span class="o">=</span><span class="p">[</span>
           <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-                <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Asset&quot;</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
+                <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Asset"</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
                 <span class="n">column_nmbr</span><span class="o">=</span><span class="n">serie</span><span class="p">,</span>
                 <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span><span class="p">,</span>
           <span class="p">)</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>  <span class="c1"># Convert returns to cumulative prices</span>
@@ -282,9 +282,9 @@ <h3>Managing Multiple Series<a class="headerlink" href="#managing-multiple-serie
 <span class="p">)</span>
 
 <span class="c1"># Frame properties</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of series: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Column names: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Common length: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of series: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">item_count</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Column names: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">columns_lvl_zero</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Common length: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -293,10 +293,10 @@ <h3>Data Alignment<a class="headerlink" href="#data-alignment" title="Link to th
 <p>OpenFrame concatenates series data but does <strong>not</strong> automatically align them.
 The library provides explicit methods for alignment that require user choice:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Series with different date ranges are concatenated (not aligned)</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Individual series lengths:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"Individual series lengths:"</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">frame</span><span class="o">.</span><span class="n">lengths_of_items</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Frame length (concatenated): </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Frame length (concatenated): </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Explicit alignment methods require user choice:</span>
 
@@ -304,14 +304,14 @@ <h3>Data Alignment<a class="headerlink" href="#data-alignment" title="Link to th
 <span class="n">frame</span><span class="o">.</span><span class="n">trunc_frame</span><span class="p">()</span>
 
 <span class="c1"># 2. Align to business day calendar (modifies original)</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">&quot;US&quot;</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">"US"</span><span class="p">)</span>
 
 <span class="c1"># 3. Handle missing values (modifies original)</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s2">&quot;fill&quot;</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s2">"fill"</span><span class="p">)</span>
 
 <span class="c1"># 4. Merge with explicit join strategy</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">merge_series</span><span class="p">(</span><span class="n">how</span><span class="o">=</span><span class="s2">&quot;inner&quot;</span><span class="p">)</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">merge_series</span><span class="p">(</span><span class="n">how</span><span class="o">=</span><span class="s2">&quot;outer&quot;</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">merge_series</span><span class="p">(</span><span class="n">how</span><span class="o">=</span><span class="s2">"inner"</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">merge_series</span><span class="p">(</span><span class="n">how</span><span class="o">=</span><span class="s2">"outer"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -336,15 +336,15 @@ <h3>Return Calculations<a class="headerlink" href="#return-calculations" title="
 <h3>Annualization<a class="headerlink" href="#annualization" title="Link to this heading"></a></h3>
 <p>Metrics are annualized using the actual number of observations per year:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Automatic calculation of periods per year</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Periods per year: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Periods per year: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">periods_in_a_year</span><span class="si">:</span><span class="s2">.1f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Annualized return (geometric mean)</span>
 <span class="n">annual_return</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized return: </span><span class="si">{</span><span class="n">annual_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized return: </span><span class="si">{</span><span class="n">annual_return</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Annualized volatility</span>
 <span class="n">annual_vol</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">vol</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized volatility: </span><span class="si">{</span><span class="n">annual_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized volatility: </span><span class="si">{</span><span class="n">annual_vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -353,19 +353,19 @@ <h3>Risk Metrics<a class="headerlink" href="#risk-metrics" title="Link to this h
 <p>Risk calculations follow industry standards:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Value at Risk (95% confidence)</span>
 <span class="n">var_95</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">var_down</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR: </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR: </span><span class="si">{</span><span class="n">var_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Conditional Value at Risk (Expected Shortfall)</span>
 <span class="n">cvar_95</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">cvar_down</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR: </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR: </span><span class="si">{</span><span class="n">cvar_95</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Maximum Drawdown</span>
 <span class="n">max_dd</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">max_drawdown</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">max_dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">max_dd</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Sortino Ratio (downside deviation)</span>
 <span class="n">sortino</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">sortino_ratio</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">sortino</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">sortino</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -375,14 +375,14 @@ <h2>Date Handling<a class="headerlink" href="#date-handling" title="Link to this
 <section id="business-day-calendars">
 <h3>Business Day Calendars<a class="headerlink" href="#business-day-calendars" title="Link to this heading"></a></h3>
 <p>openseries integrates with business day calendars:</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Align to specific country&#39;s business days (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">&quot;US&quot;</span><span class="p">)</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Align to specific country's business days (modifies original)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">"US"</span><span class="p">)</span>
 
 <span class="c1"># Multiple countries (intersection of business days) (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;US&quot;</span><span class="p">,</span> <span class="s2">&quot;GB&quot;</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">"US"</span><span class="p">,</span> <span class="s2">"GB"</span><span class="p">])</span>
 
 <span class="c1"># Custom markets using pandas-market-calendars (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">markets</span><span class="o">=</span><span class="s2">&quot;NYSE&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">markets</span><span class="o">=</span><span class="s2">"NYSE"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -390,13 +390,13 @@ <h3>Business Day Calendars<a class="headerlink" href="#business-day-calendars" t
 <h3>Resampling<a class="headerlink" href="#resampling" title="Link to this heading"></a></h3>
 <p>Convert between different frequencies:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Resample to month-end (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
 
 <span class="c1"># Resample to quarter-end (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BQE&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BQE"</span><span class="p">)</span>
 
 <span class="c1"># Custom resampling (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;W&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"W"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -409,15 +409,15 @@ <h3>Type Safety<a class="headerlink" href="#type-safety" title="Link to this hea
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Dates must be valid ISO format strings</span>
 <span class="c1"># This will fail with a validation error</span>
 <span class="n">invalid_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;invalid-date&quot;</span><span class="p">],</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s2">"invalid-date"</span><span class="p">],</span>
      <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mf">100.0</span><span class="p">]</span>
 <span class="p">)</span>
 
 <span class="c1"># Values must be numeric</span>
 <span class="c1"># This will fail with a validation error</span>
 <span class="n">invalid_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;2023-01-01&quot;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;not a number&quot;</span><span class="p">]</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s2">"2023-01-01"</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="s2">"not a number"</span><span class="p">]</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -458,8 +458,8 @@ <h3>Transformation Methods<a class="headerlink" href="#transformation-methods" t
 <span class="n">series</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>           <span class="c1"># Cumulative returns</span>
 
 <span class="c1"># Time transformations (modify original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">&quot;US&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">"US"</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>Methods that return new objects:</p>
@@ -486,8 +486,8 @@ <h3>Analysis Methods<a class="headerlink" href="#analysis-methods" title="Link t
 <h3>Export Methods<a class="headerlink" href="#export-methods" title="Link to this heading"></a></h3>
 <p>Methods for saving results:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># File exports</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s2">&quot;analysis.xlsx&quot;</span><span class="p">)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="s2">&quot;data.json&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="s2">"analysis.xlsx"</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="s2">"data.json"</span><span class="p">)</span>
 
 <span class="c1"># Visualization</span>
 <span class="n">series</span><span class="o">.</span><span class="n">plot_series</span><span class="p">()</span>
@@ -501,22 +501,22 @@ <h2>Best Practices<a class="headerlink" href="#best-practices" title="Link to th
 <section id="data-loading">
 <h3>Data Loading<a class="headerlink" href="#data-loading" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Prefer from_df for pandas data</span>
-<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">dataframe</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Asset&quot;</span><span class="p">)</span>
+<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">dataframe</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Asset"</span><span class="p">)</span>
 
 <span class="c1"># Use from_arrays for custom data</span>
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span><span class="n">dates</span><span class="o">=</span><span class="n">date_list</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">value_list</span><span class="p">)</span>
 
 <span class="c1"># Always set meaningful names</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Descriptive Name&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Descriptive Name"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="analysis-workflow">
 <h3>Analysis Workflow<a class="headerlink" href="#analysis-workflow" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># 1. Load and validate data</span>
-<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Asset&quot;</span><span class="p">)</span>
+<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Asset"</span><span class="p">)</span>
 
 <span class="c1"># 2. Basic analysis</span>
 <span class="n">metrics</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
@@ -529,7 +529,7 @@ <h3>Analysis Workflow<a class="headerlink" href="#analysis-workflow" title="Link
 <span class="n">series</span><span class="o">.</span><span class="n">plot_series</span><span class="p">()</span>
 
 <span class="c1"># 5. Export results</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">fiilename</span><span class="o">=</span><span class="s2">&quot;analysis.xlsx&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">fiilename</span><span class="o">=</span><span class="s2">"analysis.xlsx"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -539,7 +539,7 @@ <h3>Memory Management<a class="headerlink" href="#memory-management" title="Link
 <span class="n">series_copy</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_deepcopy</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
 <span class="c1"># Large datasets - consider resampling (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
 
 <span class="c1"># Clean up intermediate results</span>
 <span class="k">del</span> <span class="n">intermediate_series</span>
@@ -553,15 +553,15 @@ <h3>Portfolio Construction<a class="headerlink" href="#portfolio-construction" t
 
 <span class="c1"># Available weight strategies</span>
 <span class="n">strategies</span> <span class="o">=</span> <span class="p">{</span>
-     <span class="s1">&#39;eq_weights&#39;</span><span class="p">:</span> <span class="s1">&#39;Equal weights for all assets&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;inv_vol&#39;</span><span class="p">:</span> <span class="s1">&#39;Inverse volatility weighting (risk parity)&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;max_div&#39;</span><span class="p">:</span> <span class="s1">&#39;Maximum diversification optimization&#39;</span><span class="p">,</span>
-     <span class="s1">&#39;min_vol_overweight&#39;</span><span class="p">:</span> <span class="s1">&#39;Minimum volatility overweight strategy&#39;</span>
+     <span class="s1">'eq_weights'</span><span class="p">:</span> <span class="s1">'Equal weights for all assets'</span><span class="p">,</span>
+     <span class="s1">'inv_vol'</span><span class="p">:</span> <span class="s1">'Inverse volatility weighting (risk parity)'</span><span class="p">,</span>
+     <span class="s1">'max_div'</span><span class="p">:</span> <span class="s1">'Maximum diversification optimization'</span><span class="p">,</span>
+     <span class="s1">'min_vol_overweight'</span><span class="p">:</span> <span class="s1">'Minimum volatility overweight strategy'</span>
 <span class="p">}</span>
 
 <span class="c1"># Example with error handling</span>
 <span class="c1"># This may fail with MaxDiversificationNaNError or MaxDiversificationNegativeWeightsError</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Max Div&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;max_div&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Max Div"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"max_div"</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>Understanding these core concepts will help you use openseries effectively and build more sophisticated financial analysis workflows.</p>
diff --git a/docs/build/html/user_guide/data_handling.html b/docs/build/html/user_guide/data_handling.html
index 2e7b6471..0d3225c2 100644
--- a/docs/build/html/user_guide/data_handling.html
+++ b/docs/build/html/user_guide/data_handling.html
@@ -174,19 +174,19 @@ <h3>From pandas DataFrame/Series<a class="headerlink" href="#from-pandas-datafra
 
 <span class="c1"># From pandas Series with DatetimeIndex</span>
 <span class="n">data</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="mi">100</span><span class="p">,</span> <span class="mi">101</span><span class="p">,</span> <span class="mi">99</span><span class="p">,</span> <span class="mi">102</span><span class="p">],</span>
-                     <span class="n">index</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">4</span><span class="p">))</span>
+                     <span class="n">index</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">4</span><span class="p">))</span>
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Sample&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Sample"</span><span class="p">)</span>
 
 <span class="c1"># From pandas DataFrame column</span>
 <span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
-     <span class="s1">&#39;Date&#39;</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">4</span><span class="p">),</span>
-     <span class="s1">&#39;Close&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">101</span><span class="p">,</span> <span class="mi">99</span><span class="p">,</span> <span class="mi">102</span><span class="p">],</span>
-     <span class="s1">&#39;Volume&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">1000</span><span class="p">,</span> <span class="mi">1100</span><span class="p">,</span> <span class="mi">900</span><span class="p">,</span> <span class="mi">1200</span><span class="p">]</span>
+     <span class="s1">'Date'</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">4</span><span class="p">),</span>
+     <span class="s1">'Close'</span><span class="p">:</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">101</span><span class="p">,</span> <span class="mi">99</span><span class="p">,</span> <span class="mi">102</span><span class="p">],</span>
+     <span class="s1">'Volume'</span><span class="p">:</span> <span class="p">[</span><span class="mi">1000</span><span class="p">,</span> <span class="mi">1100</span><span class="p">,</span> <span class="mi">900</span><span class="p">,</span> <span class="mi">1200</span><span class="p">]</span>
 <span class="p">})</span>
-<span class="n">df</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s1">&#39;Date&#39;</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Stock&quot;</span><span class="p">)</span>
+<span class="n">df</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s1">'Date'</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Stock"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -194,13 +194,13 @@ <h3>From pandas DataFrame/Series<a class="headerlink" href="#from-pandas-datafra
 <h3>From Arrays<a class="headerlink" href="#from-arrays" title="Link to this heading"></a></h3>
 <p>For custom data or when working with lists:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># From date strings and values</span>
-<span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-04&#39;</span><span class="p">]</span>
+<span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">,</span> <span class="s1">'2023-01-04'</span><span class="p">]</span>
 <span class="n">values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="mf">101.0</span><span class="p">,</span> <span class="mf">99.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">]</span>
 
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
      <span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span>
      <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Custom Data&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Custom Data"</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -215,7 +215,7 @@ <h3>From Fixed Rate<a class="headerlink" href="#from-fixed-rate" title="Link to
      <span class="n">rate</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span>
      <span class="n">days</span><span class="o">=</span><span class="mi">252</span><span class="p">,</span>
      <span class="n">end_date</span><span class="o">=</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">),</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;5</span><span class="si">% F</span><span class="s2">ixed Rate&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"5</span><span class="si">% F</span><span class="s2">ixed Rate"</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -227,12 +227,12 @@ <h2>Data Validation<a class="headerlink" href="#data-validation" title="Link to
 <h3>Date Format Validation<a class="headerlink" href="#date-format-validation" title="Link to this heading"></a></h3>
 <p>openseries enforces strict date formats:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Valid date formats</span>
-<span class="n">valid_dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-12-31&#39;</span><span class="p">,</span> <span class="s1">&#39;2024-02-29&#39;</span><span class="p">]</span>  <span class="c1"># ISO format</span>
+<span class="n">valid_dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-12-31'</span><span class="p">,</span> <span class="s1">'2024-02-29'</span><span class="p">]</span>  <span class="c1"># ISO format</span>
 
 <span class="c1"># Invalid formats will raise ValidationError</span>
 <span class="c1"># This will fail with a validation error</span>
 <span class="n">invalid_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;01/01/2023&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-1-1&#39;</span><span class="p">],</span>  <span class="c1"># Wrong format</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'01/01/2023'</span><span class="p">,</span> <span class="s1">'2023-1-1'</span><span class="p">],</span>  <span class="c1"># Wrong format</span>
      <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">101</span><span class="p">]</span>
 <span class="p">)</span>
 </pre></div>
@@ -249,9 +249,9 @@ <h3>Value Validation<a class="headerlink" href="#value-validation" title="Link t
 <span class="c1"># Handle NaN values appropriately</span>
 <span class="n">values_with_nan</span> <span class="o">=</span> <span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="mf">99.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">]</span>
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-04&#39;</span><span class="p">],</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">,</span> <span class="s1">'2023-01-04'</span><span class="p">],</span>
      <span class="n">values</span><span class="o">=</span><span class="n">values_with_nan</span><span class="p">,</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Data with NaN&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Data with NaN"</span>
 <span class="p">)</span>
 
 <span class="c1"># Clean NaN values (modifies original)</span>
@@ -265,7 +265,7 @@ <h3>Length Consistency<a class="headerlink" href="#length-consistency" title="Li
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># This will raise an error</span>
 <span class="c1"># This will fail with a length mismatch error</span>
 <span class="n">invalid_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">],</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">],</span>
      <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="mf">101.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">]</span>  <span class="c1"># Different length</span>
 <span class="p">)</span>
 </pre></div>
@@ -278,14 +278,14 @@ <h2>Data Transformations<a class="headerlink" href="#data-transformations" title
 <h3>Price and Return Conversions<a class="headerlink" href="#price-and-return-conversions" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Assume we have a price series</span>
 <span class="n">prices</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">],</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">],</span>
      <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">,</span> <span class="mf">99.0</span><span class="p">],</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Stock Price&quot;</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Stock Price"</span>
 <span class="p">)</span>
 
 <span class="c1"># Convert to simple returns (modifies original)</span>
 <span class="n">prices</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Returns: </span><span class="si">{</span><span class="n">prices</span><span class="o">.</span><span class="n">values</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>  <span class="c1"># [0.02, -0.0294...]</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Returns: </span><span class="si">{</span><span class="n">prices</span><span class="o">.</span><span class="n">values</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>  <span class="c1"># [0.02, -0.0294...]</span>
 
 <span class="c1"># Convert to log returns (modifies original)</span>
 <span class="n">prices</span><span class="o">.</span><span class="n">value_to_log</span><span class="p">()</span>
@@ -302,19 +302,19 @@ <h3>Price and Return Conversions<a class="headerlink" href="#price-and-return-co
 <h3>Resampling<a class="headerlink" href="#resampling" title="Link to this heading"></a></h3>
 <p>Change the frequency of your data:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Daily to monthly (business month end) (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
 
 <span class="c1"># Daily to quarterly (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BQE&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BQE"</span><span class="p">)</span>
 
 <span class="c1"># Daily to annual (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BYE&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BYE"</span><span class="p">)</span>
 
 <span class="c1"># Custom resampling with pandas frequency strings (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;W&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"W"</span><span class="p">)</span>
 
 <span class="c1"># Resample with specific method (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;W&quot;</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">&quot;mean&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"W"</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s2">"mean"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -322,13 +322,13 @@ <h3>Resampling<a class="headerlink" href="#resampling" title="Link to this headi
 <h3>Business Day Alignment<a class="headerlink" href="#business-day-alignment" title="Link to this heading"></a></h3>
 <p>Align data to business day calendars:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Align to US business days (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">&quot;US&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">"US"</span><span class="p">)</span>
 
 <span class="c1"># Align to multiple countries (intersection) (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;US&quot;</span><span class="p">,</span> <span class="s2">&quot;GB&quot;</span><span class="p">,</span> <span class="s2">&quot;JP&quot;</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">"US"</span><span class="p">,</span> <span class="s2">"GB"</span><span class="p">,</span> <span class="s2">"JP"</span><span class="p">])</span>
 
 <span class="c1"># Align to specific market calendar (modifies original)</span>
-<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">markets</span><span class="o">=</span><span class="s2">&quot;NYSE&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">markets</span><span class="o">=</span><span class="s2">"NYSE"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -340,11 +340,11 @@ <h3>NaN Handling Strategies<a class="headerlink" href="#nan-handling-strategies"
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
 
 <span class="c1"># Create series with missing values</span>
-<span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-04&#39;</span><span class="p">]</span>
+<span class="n">dates</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">,</span> <span class="s1">'2023-01-04'</span><span class="p">]</span>
 <span class="n">values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">100.0</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="mf">102.0</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">]</span>
 
 <span class="n">series_with_nan</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;With NaN&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="n">dates</span><span class="p">,</span> <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"With NaN"</span>
 <span class="p">)</span>
 
 <span class="c1"># Forward fill missing values (for price series) (modifies original)</span>
@@ -359,7 +359,7 @@ <h3>NaN Handling Strategies<a class="headerlink" href="#nan-handling-strategies"
 <section id="dropping-missing-data">
 <h3>Dropping Missing Data<a class="headerlink" href="#dropping-missing-data" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Remove NaN values entirely (modifies original)</span>
-<span class="n">series_with_nan</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s2">&quot;drop&quot;</span><span class="p">)</span>
+<span class="n">series_with_nan</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s2">"drop"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -372,13 +372,13 @@ <h3>Creating OpenFrame<a class="headerlink" href="#creating-openframe" title="Li
 
 <span class="c1"># Create multiple series</span>
 <span class="n">series1</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">102</span><span class="p">,</span> <span class="mi">99</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Asset A&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">102</span><span class="p">,</span> <span class="mi">99</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Asset A"</span>
 <span class="p">)</span>
 
 <span class="n">series2</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">50</span><span class="p">,</span> <span class="mi">51</span><span class="p">,</span> <span class="mi">49</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Asset B&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">50</span><span class="p">,</span> <span class="mi">51</span><span class="p">,</span> <span class="mi">49</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Asset B"</span>
 <span class="p">)</span>
 
 <span class="c1"># Create frame</span>
@@ -391,18 +391,18 @@ <h3>Handling Different Date Ranges<a class="headerlink" href="#handling-differen
 <p>OpenFrame automatically handles series with different date ranges:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Series with different start/end dates</span>
 <span class="n">early_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2022-12-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">95</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">102</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Early Start&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2022-12-01'</span><span class="p">,</span> <span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">95</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">102</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Early Start"</span>
 <span class="p">)</span>
 
 <span class="n">late_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-04&#39;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">51</span><span class="p">,</span> <span class="mi">49</span><span class="p">,</span> <span class="mi">52</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Late Start&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">,</span> <span class="s1">'2023-01-04'</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">51</span><span class="p">,</span> <span class="mi">49</span><span class="p">,</span> <span class="mi">52</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Late Start"</span>
 <span class="p">)</span>
 
 <span class="c1"># Frame will align to common date range</span>
 <span class="n">frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="p">[</span><span class="n">early_series</span><span class="p">,</span> <span class="n">late_series</span><span class="p">])</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Frame date range: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Frame date range: </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">frame</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -410,8 +410,8 @@ <h3>Handling Different Date Ranges<a class="headerlink" href="#handling-differen
 <h3>Adding and Removing Series<a class="headerlink" href="#adding-and-removing-series" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Add a new series</span>
 <span class="n">new_series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_arrays</span><span class="p">(</span>
-     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;2023-01-01&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-02&#39;</span><span class="p">,</span> <span class="s1">&#39;2023-01-03&#39;</span><span class="p">],</span>
-     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">200</span><span class="p">,</span> <span class="mi">205</span><span class="p">,</span> <span class="mi">198</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Asset C&quot;</span>
+     <span class="n">dates</span><span class="o">=</span><span class="p">[</span><span class="s1">'2023-01-01'</span><span class="p">,</span> <span class="s1">'2023-01-02'</span><span class="p">,</span> <span class="s1">'2023-01-03'</span><span class="p">],</span>
+     <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">200</span><span class="p">,</span> <span class="mi">205</span><span class="p">,</span> <span class="mi">198</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Asset C"</span>
 <span class="p">)</span>
 <span class="n">frame</span><span class="o">.</span><span class="n">add_timeseries</span><span class="p">(</span><span class="n">new_series</span><span class="p">)</span>
 
@@ -426,15 +426,15 @@ <h2>Data Export and Import<a class="headerlink" href="#data-export-and-import" t
 <section id="excel-export">
 <h3>Excel Export<a class="headerlink" href="#excel-export" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export single series</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">&quot;single_series.xlsx&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">"single_series.xlsx"</span><span class="p">)</span>
 
 <span class="c1"># Export frame (multiple series)</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">&quot;multiple_series.xlsx&quot;</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">"multiple_series.xlsx"</span><span class="p">)</span>
 
 <span class="c1"># Export with custom sheet title</span>
 <span class="n">series</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span>
-     <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;formatted_export.xlsx&quot;</span><span class="p">,</span>
-     <span class="n">sheet_title</span><span class="o">=</span><span class="s2">&quot;Analysis&quot;</span>
+     <span class="n">filename</span><span class="o">=</span><span class="s2">"formatted_export.xlsx"</span><span class="p">,</span>
+     <span class="n">sheet_title</span><span class="o">=</span><span class="s2">"Analysis"</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -442,13 +442,13 @@ <h3>Excel Export<a class="headerlink" href="#excel-export" title="Link to this h
 <section id="json-export">
 <h3>JSON Export<a class="headerlink" href="#json-export" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export series values only</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">&quot;values&quot;</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;series_values.json&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">"values"</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">"series_values.json"</span><span class="p">)</span>
 
 <span class="c1"># Export full dataframe structure</span>
-<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">&quot;tsdf&quot;</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;series_dataframe.json&quot;</span><span class="p">)</span>
+<span class="n">series</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">"tsdf"</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">"series_dataframe.json"</span><span class="p">)</span>
 
 <span class="c1"># Export frame data</span>
-<span class="n">frame</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">&quot;values&quot;</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;frame_values.json&quot;</span><span class="p">)</span>
+<span class="n">frame</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">what_output</span><span class="o">=</span><span class="s2">"values"</span><span class="p">,</span> <span class="n">filename</span><span class="o">=</span><span class="s2">"frame_values.json"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -460,23 +460,23 @@ <h3>Yahoo Finance Integration<a class="headerlink" href="#yahoo-finance-integrat
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">yfinance</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">yf</span>
 
 <span class="c1"># Single asset</span>
-<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;AAPL&quot;</span><span class="p">)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;2y&quot;</span><span class="p">)</span>
+<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"AAPL"</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"2y"</span><span class="p">)</span>
 
 <span class="n">apple</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">],</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Apple Inc.&quot;</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">],</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Apple Inc."</span>
 <span class="p">)</span>
 
 <span class="c1"># Multiple assets</span>
-<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="s2">&quot;GOOGL&quot;</span><span class="p">,</span> <span class="s2">&quot;MSFT&quot;</span><span class="p">]</span>
+<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"AAPL"</span><span class="p">,</span> <span class="s2">"GOOGL"</span><span class="p">,</span> <span class="s2">"MSFT"</span><span class="p">]</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 
 <span class="k">for</span> <span class="n">ticker_symbol</span> <span class="ow">in</span> <span class="n">tickers</span><span class="p">:</span>
      <span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker_symbol</span><span class="p">)</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;1y&quot;</span><span class="p">)</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"1y"</span><span class="p">)</span>
      <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">],</span>
+          <span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">],</span>
           <span class="n">name</span><span class="o">=</span><span class="n">ticker_symbol</span>
      <span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
@@ -488,11 +488,11 @@ <h3>Yahoo Finance Integration<a class="headerlink" href="#yahoo-finance-integrat
 <section id="csv-data">
 <h3>CSV Data<a class="headerlink" href="#csv-data" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Load from CSV</span>
-<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;stock_data.csv&quot;</span><span class="p">,</span> <span class="n">index_col</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">parse_dates</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"stock_data.csv"</span><span class="p">,</span> <span class="n">index_col</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">parse_dates</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
 
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">],</span>
-     <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Stock from CSV&quot;</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">],</span>
+     <span class="n">name</span><span class="o">=</span><span class="s2">"Stock from CSV"</span>
 <span class="p">)</span>
 </pre></div>
 </div>
@@ -503,16 +503,16 @@ <h2>Data Quality Checks<a class="headerlink" href="#data-quality-checks" title="
 <section id="validation-methods">
 <h3>Validation Methods<a class="headerlink" href="#validation-methods" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Check for data quality issues</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Date range: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Span of days: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">span_of_days</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Span of days: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">span_of_days</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Check for gaps in data</span>
 <span class="n">expected_length</span> <span class="o">=</span> <span class="p">(</span><span class="n">series</span><span class="o">.</span><span class="n">last_idx</span> <span class="o">-</span> <span class="n">series</span><span class="o">.</span><span class="n">first_idx</span><span class="p">)</span><span class="o">.</span><span class="n">days</span> <span class="o">+</span> <span class="mi">1</span>
 <span class="n">actual_length</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">length</span>
 
 <span class="k">if</span> <span class="n">expected_length</span> <span class="o">!=</span> <span class="n">actual_length</span><span class="p">:</span>
-     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Data gaps detected: expected </span><span class="si">{</span><span class="n">expected_length</span><span class="si">}</span><span class="s2">, got </span><span class="si">{</span><span class="n">actual_length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+     <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Data gaps detected: expected </span><span class="si">{</span><span class="n">expected_length</span><span class="si">}</span><span class="s2">, got </span><span class="si">{</span><span class="n">actual_length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -523,11 +523,11 @@ <h3>Outlier Detection<a class="headerlink" href="#outlier-detection" title="Link
 
 <span class="c1"># Detect outliers using the built-in method</span>
 <span class="n">outliers</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">outliers</span><span class="p">(</span><span class="n">threshold</span><span class="o">=</span><span class="mf">3.0</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Found </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">outliers</span><span class="p">)</span><span class="si">}</span><span class="s2"> outliers (|z| &gt; 3)&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Found </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">outliers</span><span class="p">)</span><span class="si">}</span><span class="s2"> outliers (|z| &gt; 3)"</span><span class="p">)</span>
 
 <span class="c1"># For OpenFrame, outliers returns a DataFrame</span>
 <span class="n">frame_outliers</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">outliers</span><span class="p">(</span><span class="n">threshold</span><span class="o">=</span><span class="mf">3.0</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Found outliers in frame: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frame_outliers</span><span class="p">)</span><span class="si">}</span><span class="s2"> rows&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Found outliers in frame: </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">frame_outliers</span><span class="p">)</span><span class="si">}</span><span class="s2"> rows"</span><span class="p">)</span>
 
 <span class="c1"># Customize threshold and date range</span>
 <span class="n">recent_outliers</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">outliers</span><span class="p">(</span>
@@ -546,7 +546,7 @@ <h3>Memory Usage<a class="headerlink" href="#memory-usage" title="Link to this h
 <span class="n">large_series</span> <span class="o">=</span> <span class="n">series</span>  <span class="c1"># Assume this is large daily data</span>
 
 <span class="c1"># Reduce to monthly for analysis (modifies original)</span>
-<span class="n">large_series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
+<span class="n">large_series</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
 
 <span class="c1"># Use monthly for computationally intensive operations</span>
 <span class="n">monthly_metrics</span> <span class="o">=</span> <span class="n">large_series</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
@@ -556,10 +556,10 @@ <h3>Memory Usage<a class="headerlink" href="#memory-usage" title="Link to this h
 <section id="efficient-data-loading">
 <h3>Efficient Data Loading<a class="headerlink" href="#efficient-data-loading" title="Link to this heading"></a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># When loading multiple assets, batch the operations</span>
-<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;AAPL&quot;</span><span class="p">,</span> <span class="s2">&quot;GOOGL&quot;</span><span class="p">,</span> <span class="s2">&quot;MSFT&quot;</span><span class="p">,</span> <span class="s2">&quot;AMZN&quot;</span><span class="p">,</span> <span class="s2">&quot;TSLA&quot;</span><span class="p">]</span>
+<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"AAPL"</span><span class="p">,</span> <span class="s2">"GOOGL"</span><span class="p">,</span> <span class="s2">"MSFT"</span><span class="p">,</span> <span class="s2">"AMZN"</span><span class="p">,</span> <span class="s2">"TSLA"</span><span class="p">]</span>
 
 <span class="c1"># Download all at once</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">download</span><span class="p">(</span><span class="n">tickers</span><span class="p">,</span> <span class="n">period</span><span class="o">=</span><span class="s2">&quot;2y&quot;</span><span class="p">)[</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">download</span><span class="p">(</span><span class="n">tickers</span><span class="p">,</span> <span class="n">period</span><span class="o">=</span><span class="s2">"2y"</span><span class="p">)[</span><span class="s1">'Close'</span><span class="p">]</span>
 
 <span class="c1"># Create series efficiently</span>
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
diff --git a/docs/build/html/user_guide/installation.html b/docs/build/html/user_guide/installation.html
index bfb1687f..2a45baed 100644
--- a/docs/build/html/user_guide/installation.html
+++ b/docs/build/html/user_guide/installation.html
@@ -184,7 +184,7 @@ <h3>Core Dependencies<a class="headerlink" href="#core-dependencies" title="Link
 <li><p><strong>pandas</strong> (&gt;=2.1.2,&lt;3.0.0) - Data manipulation and analysis</p></li>
 <li><p><strong>numpy</strong> (&gt;=1.23.2,!=2.3.0,&lt;3.0.0) - Numerical computing</p></li>
 <li><p><strong>pydantic</strong> (&gt;=2.5.2,&lt;3.0.0) - Data validation and settings management</p></li>
-<li><p><strong>plotly</strong> (&gt;=5.18.0,&lt;7.0.0) - Interactive plotting</p></li>
+<li><p><strong>plotly</strong> (&gt;=5.18.0) - Interactive plotting</p></li>
 <li><p><strong>scipy</strong> (&gt;=1.11.4,&lt;2.0.0) - Scientific computing</p></li>
 <li><p><strong>scikit-learn</strong> (&gt;=1.4.0,&lt;2.0.0) - Machine learning utilities</p></li>
 </ul>
@@ -235,12 +235,12 @@ <h2>Verifying Installation<a class="headerlink" href="#verifying-installation" t
 
 <span class="c1"># Create OpenTimeSeries</span>
 <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Test Series&quot;</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Test Series"</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
      <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
 <span class="p">)</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>  <span class="c1"># Convert returns to cumulative prices</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annual return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Series length: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annual return: </span><span class="si">{</span><span class="n">series</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -256,7 +256,7 @@ <h2>Development Installation<a class="headerlink" href="#development-installatio
 <span class="c1"># Create a virtual environment and install dependencies</span>
 uv<span class="w"> </span>venv<span class="w"> </span>venv
 <span class="nb">source</span><span class="w"> </span>venv/bin/activate
-uv<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span><span class="s2">&quot;.[dev]&quot;</span>
+uv<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span><span class="s2">".[dev]"</span>
 </pre></div>
 </div>
 <p>This will install additional development dependencies including:</p>
diff --git a/docs/build/html/user_guide/quickstart.html b/docs/build/html/user_guide/quickstart.html
index eadd20a5..abf3c0f1 100644
--- a/docs/build/html/user_guide/quickstart.html
+++ b/docs/build/html/user_guide/quickstart.html
@@ -148,17 +148,17 @@ <h2>Your First OpenTimeSeries<a class="headerlink" href="#your-first-opentimeser
 
 <span class="c1"># Convert simulation to OpenTimeSeries</span>
 <span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span>
-     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
+     <span class="n">dframe</span><span class="o">=</span><span class="n">simulation</span><span class="o">.</span><span class="n">to_dataframe</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"S&amp;P 500"</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="n">dt</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2023</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="mi">31</span><span class="p">)),</span>
      <span class="n">valuetype</span><span class="o">=</span><span class="n">ValueType</span><span class="o">.</span><span class="n">RTRN</span>
 <span class="p">)</span><span class="o">.</span><span class="n">to_cumret</span><span class="p">()</span>  <span class="c1"># Convert returns to cumulative prices</span>
 
-<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"S&amp;P 500"</span><span class="p">)</span>
 
 <span class="c1"># Display basic information</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Series: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Start date: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;End date: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Number of observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Series: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">label</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Start date: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"End date: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Number of observations: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -169,17 +169,17 @@ <h2>Loading Data from External Sources<a class="headerlink" href="#loading-data-
 <span class="kn">from</span><span class="w"> </span><span class="nn">openseries</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenTimeSeries</span>
 
 <span class="c1"># Download S&amp;P 500 data</span>
-<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">&quot;^GSPC&quot;</span><span class="p">)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;2y&quot;</span><span class="p">)</span>
+<span class="n">ticker</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="s2">"^GSPC"</span><span class="p">)</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"2y"</span><span class="p">)</span>
 
 <span class="c1"># Create OpenTimeSeries from the Close prices</span>
-<span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+<span class="n">sp500</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
 
 <span class="c1"># Set a more descriptive label</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;S&amp;P 500 Index&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"S&amp;P 500 Index"</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Loaded </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Date range: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Loaded </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2"> observations"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Date range: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">first_idx</span><span class="si">}</span><span class="s2"> to </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">last_idx</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -187,21 +187,21 @@ <h2>Loading Data from External Sources<a class="headerlink" href="#loading-data-
 <h2>Basic Financial Metrics<a class="headerlink" href="#basic-financial-metrics" title="Link to this heading"></a></h2>
 <p>openseries provides a comprehensive set of financial metrics:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Key performance metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Return (CAGR): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Annualized Volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sharpe Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Maximum Drawdown: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Total Return: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">value_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Return (CAGR): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Annualized Volatility: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sharpe Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Maximum Drawdown: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">max_drawdown</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Risk metrics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% VaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;95% CVaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Sortino Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% VaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">var_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"95% CVaR (daily): </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">cvar_down</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Sortino Ratio: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">sortino_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Distribution statistics</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Skewness: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Kurtosis: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Positive Days: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Skewness: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">skew</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Kurtosis: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">kurtosis</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Positive Days: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">positive_share</span><span class="si">:</span><span class="s2">.1%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 <section id="get-all-metrics-at-once">
@@ -242,13 +242,13 @@ <h2>Working with Multiple Assets (OpenFrame)<a class="headerlink" href="#working
 <span class="kn">import</span><span class="w"> </span><span class="nn">yfinance</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">yf</span>
 
 <span class="c1"># Download data for multiple assets</span>
-<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;^GSPC&quot;</span><span class="p">,</span> <span class="s2">&quot;^IXIC&quot;</span><span class="p">,</span> <span class="s2">&quot;^RUT&quot;</span><span class="p">]</span>  <span class="c1"># S&amp;P 500, NASDAQ, Russell 2000</span>
-<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;S&amp;P 500&quot;</span><span class="p">,</span> <span class="s2">&quot;NASDAQ&quot;</span><span class="p">,</span> <span class="s2">&quot;Russell 2000&quot;</span><span class="p">]</span>
+<span class="n">tickers</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"^GSPC"</span><span class="p">,</span> <span class="s2">"^IXIC"</span><span class="p">,</span> <span class="s2">"^RUT"</span><span class="p">]</span>  <span class="c1"># S&amp;P 500, NASDAQ, Russell 2000</span>
+<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"S&amp;P 500"</span><span class="p">,</span> <span class="s2">"NASDAQ"</span><span class="p">,</span> <span class="s2">"Russell 2000"</span><span class="p">]</span>
 
 <span class="n">series_list</span> <span class="o">=</span> <span class="p">[]</span>
 <span class="k">for</span> <span class="n">ticker</span><span class="p">,</span> <span class="n">name</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">tickers</span><span class="p">,</span> <span class="n">names</span><span class="p">):</span>
-     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">&quot;2y&quot;</span><span class="p">)</span>
-     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
+     <span class="n">data</span> <span class="o">=</span> <span class="n">yf</span><span class="o">.</span><span class="n">Ticker</span><span class="p">(</span><span class="n">ticker</span><span class="p">)</span><span class="o">.</span><span class="n">history</span><span class="p">(</span><span class="n">period</span><span class="o">=</span><span class="s2">"2y"</span><span class="p">)</span>
+     <span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
      <span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="n">name</span><span class="p">)</span>
      <span class="n">series_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
 
@@ -262,7 +262,7 @@ <h2>Working with Multiple Assets (OpenFrame)<a class="headerlink" href="#working
 
 <span class="c1"># Calculate correlations</span>
 <span class="n">correlations</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">correl_matrix</span>
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Correlation Matrix:&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">Correlation Matrix:"</span><span class="p">)</span>
 <span class="nb">print</span><span class="p">(</span><span class="n">correlations</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -271,18 +271,18 @@ <h2>Working with Multiple Assets (OpenFrame)<a class="headerlink" href="#working
 <h2>Portfolio Analysis<a class="headerlink" href="#portfolio-analysis" title="Link to this heading"></a></h2>
 <p>Create and analyze portfolios:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Equal-weighted portfolio</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Equal Weight Portfolio Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Return: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">geo_ret</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Volatility: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">vol</span><span class="si">:</span><span class="s2">.2%</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Equal Weight Portfolio Sharpe: </span><span class="si">{</span><span class="n">portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Create custom weighted portfolio</span>
 <span class="n">frame</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.8</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">]</span>  <span class="c1"># Custom allocation</span>
-<span class="n">custom_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Custom Portfolio&quot;</span><span class="p">)</span>
+<span class="n">custom_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Custom Portfolio"</span><span class="p">)</span>
 <span class="n">custom_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">custom_df</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Custom Portfolio Sharpe: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Custom Portfolio Sharpe: </span><span class="si">{</span><span class="n">custom_portfolio</span><span class="o">.</span><span class="n">ret_vol_ratio</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Compare with individual assets</span>
 <span class="n">frame</span><span class="o">.</span><span class="n">add_timeseries</span><span class="p">(</span><span class="n">portfolio</span><span class="p">)</span>
@@ -297,7 +297,7 @@ <h2>Data Transformations<a class="headerlink" href="#data-transformations" title
 <p>openseries provides various data transformation methods:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Convert prices to returns (modifies original)</span>
 <span class="n">sp500</span><span class="o">.</span><span class="n">value_to_ret</span><span class="p">()</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Returns series length: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Returns series length: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 
 <span class="c1"># Convert to log returns (modifies original)</span>
 <span class="n">sp500</span><span class="o">.</span><span class="n">value_to_log</span><span class="p">()</span>
@@ -307,8 +307,8 @@ <h2>Data Transformations<a class="headerlink" href="#data-transformations" title
 <span class="n">rolling_ret</span> <span class="o">=</span> <span class="n">sp500</span><span class="o">.</span><span class="n">rolling_return</span><span class="p">(</span><span class="n">observations</span><span class="o">=</span><span class="mi">30</span><span class="p">)</span>  <span class="c1"># 30-day rolling returns</span>
 
 <span class="c1"># Resample to monthly data (modifies original)</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">&quot;BME&quot;</span><span class="p">)</span>
-<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Monthly data points: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">resample_to_business_period_ends</span><span class="p">(</span><span class="n">freq</span><span class="o">=</span><span class="s2">"BME"</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Monthly data points: </span><span class="si">{</span><span class="n">sp500</span><span class="o">.</span><span class="n">length</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -316,10 +316,10 @@ <h2>Data Transformations<a class="headerlink" href="#data-transformations" title
 <h2>Exporting Results<a class="headerlink" href="#exporting-results" title="Link to this heading"></a></h2>
 <p>Save your analysis results:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Export to Excel</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">&quot;sp500_analysis.xlsx&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">to_xlsx</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">"sp500_analysis.xlsx"</span><span class="p">)</span>
 
 <span class="c1"># Export to JSON</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">&quot;sp500_data.json&quot;</span><span class="p">,</span> <span class="n">what_output</span><span class="o">=</span><span class="s2">&quot;tsdf&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">to_json</span><span class="p">(</span><span class="n">filename</span><span class="o">=</span><span class="s2">"sp500_data.json"</span><span class="p">,</span> <span class="n">what_output</span><span class="o">=</span><span class="s2">"tsdf"</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
@@ -327,10 +327,10 @@ <h2>Exporting Results<a class="headerlink" href="#exporting-results" title="Link
 <h2>Working with Business Days<a class="headerlink" href="#working-with-business-days" title="Link to this heading"></a></h2>
 <p>openseries handles business day calendars automatically:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Align to Swedish business days (modifies original)</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">&quot;SE&quot;</span><span class="p">)</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="s2">"SE"</span><span class="p">)</span>
 
 <span class="c1"># Use multiple countries (modifies original)</span>
-<span class="n">sp500</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;US&quot;</span><span class="p">,</span> <span class="s2">&quot;GB&quot;</span><span class="p">])</span>
+<span class="n">sp500</span><span class="o">.</span><span class="n">align_index_to_local_cdays</span><span class="p">(</span><span class="n">countries</span><span class="o">=</span><span class="p">[</span><span class="s2">"US"</span><span class="p">,</span> <span class="s2">"GB"</span><span class="p">])</span>
 
 <span class="c1"># Handle missing values (modifies original)</span>
 <span class="n">sp500</span><span class="o">.</span><span class="n">value_nan_handle</span><span class="p">()</span>  <span class="c1"># Forward fill NaN values</span>
@@ -361,8 +361,8 @@ <h2>Key Concepts to Remember<a class="headerlink" href="#key-concepts-to-remembe
 <h2>Common Patterns<a class="headerlink" href="#common-patterns" title="Link to this heading"></a></h2>
 <p>Here are some common usage patterns:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Pattern 1: Load, analyze, visualize</span>
-<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span>
-<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">&quot;Asset&quot;</span><span class="p">)</span>
+<span class="n">series</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s1">'Close'</span><span class="p">])</span>
+<span class="n">series</span><span class="o">.</span><span class="n">set_new_label</span><span class="p">(</span><span class="n">lvl_zero</span><span class="o">=</span><span class="s2">"Asset"</span><span class="p">)</span>
 <span class="n">metrics</span> <span class="o">=</span> <span class="n">series</span><span class="o">.</span><span class="n">all_properties</span><span class="p">()</span>
 <span class="n">series</span><span class="o">.</span><span class="n">plot_series</span><span class="p">()</span>
 
@@ -372,14 +372,14 @@ <h2>Common Patterns<a class="headerlink" href="#common-patterns" title="Link to
 <span class="n">correlations</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">correl_matrix</span>
 
 <span class="c1"># Pattern 3: Portfolio construction (built-in strategies)</span>
-<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Equal Weight&quot;</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">&quot;eq_weights&quot;</span><span class="p">)</span>
+<span class="n">portfolio_df</span> <span class="o">=</span> <span class="n">frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Equal Weight"</span><span class="p">,</span> <span class="n">weight_strat</span><span class="o">=</span><span class="s2">"eq_weights"</span><span class="p">)</span>
 <span class="n">portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">portfolio_df</span><span class="p">)</span>
 <span class="n">frame</span><span class="o">.</span><span class="n">add_timeseries</span><span class="p">(</span><span class="n">portfolio</span><span class="p">)</span>
 
 <span class="c1"># Pattern 3b: Custom portfolio construction (create fresh frame)</span>
 <span class="n">custom_frame</span> <span class="o">=</span> <span class="n">OpenFrame</span><span class="p">(</span><span class="n">constituents</span><span class="o">=</span><span class="p">[</span><span class="n">series1</span><span class="p">,</span> <span class="n">series2</span><span class="p">,</span> <span class="n">series3</span><span class="p">])</span>
 <span class="n">custom_frame</span><span class="o">.</span><span class="n">weights</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.4</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">]</span>
-<span class="n">custom_df</span> <span class="o">=</span> <span class="n">custom_frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Custom Portfolio&quot;</span><span class="p">)</span>
+<span class="n">custom_df</span> <span class="o">=</span> <span class="n">custom_frame</span><span class="o">.</span><span class="n">make_portfolio</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Custom Portfolio"</span><span class="p">)</span>
 <span class="n">custom_portfolio</span> <span class="o">=</span> <span class="n">OpenTimeSeries</span><span class="o">.</span><span class="n">from_df</span><span class="p">(</span><span class="n">dframe</span><span class="o">=</span><span class="n">custom_df</span><span class="p">)</span>
 
 <span class="c1"># Pattern 4: Risk analysis</span>
diff --git a/docs/source/user_guide/installation.rst b/docs/source/user_guide/installation.rst
index 9561e284..3ae5fc99 100644
--- a/docs/source/user_guide/installation.rst
+++ b/docs/source/user_guide/installation.rst
@@ -52,7 +52,7 @@ Core Dependencies
 - **pandas** (>=2.1.2,<3.0.0) - Data manipulation and analysis
 - **numpy** (>=1.23.2,!=2.3.0,<3.0.0) - Numerical computing
 - **pydantic** (>=2.5.2,<3.0.0) - Data validation and settings management
-- **plotly** (>=5.18.0,<7.0.0) - Interactive plotting
+- **plotly** (>=5.18.0) - Interactive plotting
 - **scipy** (>=1.11.4,<2.0.0) - Scientific computing
 - **scikit-learn** (>=1.4.0,<2.0.0) - Machine learning utilities
 
diff --git a/openseries/_common_model.py b/openseries/_common_model.py
index 44570bf9..07ceecdd 100644
--- a/openseries/_common_model.py
+++ b/openseries/_common_model.py
@@ -14,7 +14,7 @@
 from string import ascii_letters
 from typing import TYPE_CHECKING, Any, Generic, Literal, Self, cast
 
-from numpy import asarray, float64, inf, isnan, log, maximum, sqrt
+from numpy import asarray, float64, inf, isnan, linspace, log, maximum, sqrt
 
 from .owntypes import (
     CaptorLogoType,
@@ -58,10 +58,10 @@
     to_datetime,
 )
 from pandas.tseries.offsets import CustomBusinessDay
-from plotly.figure_factory import create_distplot  # type: ignore[import-untyped]
 from plotly.graph_objs import Figure  # type: ignore[import-untyped]
 from pydantic import BaseModel, ConfigDict, DirectoryPath, Field
 from scipy.stats import (
+    gaussian_kde,
     kurtosis,
     norm,
     skew,
@@ -210,6 +210,111 @@ def _calculate_time_factor(
     return data.count() / fraction
 
 
+_DISTPLOT_COLORS = (
+    "rgb(31, 119, 180)",
+    "rgb(255, 127, 14)",
+    "rgb(44, 160, 44)",
+    "rgb(214, 39, 40)",
+    "rgb(148, 103, 189)",
+    "rgb(140, 86, 75)",
+    "rgb(227, 119, 194)",
+    "rgb(127, 127, 127)",
+    "rgb(188, 189, 34)",
+    "rgb(23, 190, 207)",
+)
+_DISTPLOT_CURVE_POINTS = 500
+_DISTPLOT_BIN_SIZE = 1.0
+
+
+def _create_distplot(
+    hist_data: list[Series[float]],
+    group_labels: list[str],
+    curve_type: LiteralPlotlyHistogramCurveType,
+    histnorm: LiteralPlotlyHistogramHistNorm,
+    *,
+    show_rug: bool,
+) -> Figure:
+    """Create a distribution curve figure compatible with Plotly 6 and 7.
+
+    Replaces ``plotly.figure_factory.create_distplot``, which was removed in
+    Plotly 7, for the ``plot_histogram(..., plot_type="lines")`` path.
+
+    Args:
+        hist_data: One series of observations per trace.
+        group_labels: Legend names aligned with ``hist_data``.
+        curve_type: ``"kde"`` or ``"normal"`` overlay.
+        histnorm: Histogram normalization; ``"probability"`` scales the curve
+            by the default bin size as ``create_distplot`` did.
+        show_rug: If True, add a rug plot on a secondary y-axis.
+
+    Returns:
+        A Plotly Figure of scatter line traces (and optional rug traces).
+    """
+    curve_traces: list[dict[str, Any]] = []
+    rug_traces: list[dict[str, Any]] = []
+    for index, series in enumerate(hist_data):
+        values = asarray(series, dtype=float64)
+        start = float(min(series))
+        end = float(max(series))
+        curve_x = linspace(start, end, _DISTPLOT_CURVE_POINTS, endpoint=False)
+        if curve_type == "normal":
+            loc, scale = norm.fit(values)
+            curve_y = norm.pdf(curve_x, loc=loc, scale=scale)
+        else:
+            curve_y = gaussian_kde(values)(curve_x)
+        if histnorm == "probability":
+            curve_y = curve_y * _DISTPLOT_BIN_SIZE
+        color = _DISTPLOT_COLORS[index % len(_DISTPLOT_COLORS)]
+        label = group_labels[index]
+        curve_traces.append(
+            {
+                "type": "scatter",
+                "x": curve_x,
+                "y": curve_y,
+                "xaxis": "x1",
+                "yaxis": "y1",
+                "mode": "lines",
+                "name": label,
+                "legendgroup": label,
+                "showlegend": True,
+                "marker": {"color": color},
+            },
+        )
+        if show_rug:
+            rug_traces.append(
+                {
+                    "type": "scatter",
+                    "x": values,
+                    "y": [label] * len(values),
+                    "xaxis": "x1",
+                    "yaxis": "y2",
+                    "mode": "markers",
+                    "name": label,
+                    "legendgroup": label,
+                    "showlegend": False,
+                    "marker": {"color": color, "symbol": "line-ns-open"},
+                },
+            )
+
+    layout: dict[str, Any] = {
+        "barmode": "overlay",
+        "hovermode": "closest",
+        "legend": {"traceorder": "reversed"},
+        "xaxis1": {"domain": [0.0, 1.0], "anchor": "y2", "zeroline": False},
+        "yaxis1": {"domain": [0.0, 1], "anchor": "free", "position": 0.0},
+    }
+    if show_rug:
+        layout["yaxis1"] = {"domain": [0.35, 1], "anchor": "free", "position": 0.0}
+        layout["yaxis2"] = {
+            "domain": [0, 0.25],
+            "anchor": "x1",
+            "dtick": 1,
+            "showticklabels": False,
+        }
+
+    return Figure(data=curve_traces + rug_traces, layout=layout)
+
+
 class _CommonModel(BaseModel, Generic[SeriesOrFloat_co]):
     """Declare _CommonModel."""
 
@@ -1437,13 +1542,12 @@ def plot_histogram(
             )
         elif plot_type == "lines":
             hist_data = [self.tsdf[col] for col in self.tsdf.columns]
-            figure = create_distplot(
+            figure = _create_distplot(
                 hist_data=hist_data,
-                curve_type=curve_type,
                 group_labels=labels,
-                show_hist=False,
-                show_rug=show_rug,
+                curve_type=curve_type,
                 histnorm=histnorm,
+                show_rug=show_rug,
             )
             figure.update_layout(dict1=fig_dict["layout"])
         else:
diff --git a/tests/test_common_model_internals.py b/tests/test_common_model_internals.py
index edf55026..8885ab23 100644
--- a/tests/test_common_model_internals.py
+++ b/tests/test_common_model_internals.py
@@ -10,7 +10,7 @@
 from numpy import float64
 from pandas import DataFrame, MultiIndex, Series
 
-from openseries._common_model import _CommonModel
+from openseries._common_model import _CommonModel, _create_distplot
 from openseries.owntypes import ValueType
 
 _EXPECTED_SCALAR = 0.25
@@ -75,3 +75,58 @@ def test_get_or_set_countries_get_raises_without_constituents() -> None:
     raw = _CommonModel[float].model_construct(tsdf=DataFrame(dtype="float64"))
     with pytest.raises(TypeError, match="Cannot get countries without constituents"):
         raw._get_or_set_countries(None)
+
+
+def _distplot_sample_series() -> Series[float]:
+    return Series([1.0, 1.2, 1.1, 2.0, 2.1, 1.9, 3.0, 2.8], dtype=float64)
+
+
+def test_create_distplot_kde_without_rug() -> None:
+    """KDE lines plot emits one legend scatter trace and no rug axis."""
+    fig = _create_distplot(
+        hist_data=[_distplot_sample_series()],
+        group_labels=["alpha"],
+        curve_type="kde",
+        histnorm="probability",
+        show_rug=False,
+    )
+    if len(fig.data) != 1:
+        msg = f"Expected a single curve trace, got {len(fig.data)}"
+        raise AssertionError(msg)
+    trace = fig.data[0].to_plotly_json()
+    if trace["type"] != "scatter" or trace["mode"] != "lines":
+        msg = f"Unexpected curve trace: type={trace['type']} mode={trace['mode']}"
+        raise AssertionError(msg)
+    if trace["name"] != "alpha":
+        msg = f"Unexpected trace name: {trace['name']}"
+        raise AssertionError(msg)
+    if "yaxis2" in fig.to_dict()["layout"]:
+        msg = "Rug y-axis should be absent when show_rug is False"
+        raise AssertionError(msg)
+
+
+def test_create_distplot_normal_with_rug() -> None:
+    """Normal curve plus rug uses a secondary axis and hides the rug legend."""
+    labels = ["alpha", "beta"]
+    fig = _create_distplot(
+        hist_data=[_distplot_sample_series(), _distplot_sample_series() + 1.0],
+        group_labels=labels,
+        curve_type="normal",
+        histnorm="probability density",
+        show_rug=True,
+    )
+    expected_traces = len(labels) * 2
+    if len(fig.data) != expected_traces:
+        msg = f"Expected two curve traces and two rug traces, got {len(fig.data)}"
+        raise AssertionError(msg)
+    curve_names = [trace["name"] for trace in fig.data[:2]]
+    if curve_names != labels:
+        msg = f"Curve labels mismatch: {curve_names}"
+        raise AssertionError(msg)
+    rug = fig.data[2].to_plotly_json()
+    if rug["mode"] != "markers" or rug["showlegend"] is not False:
+        msg = "Rug traces must be unmarked in the legend"
+        raise AssertionError(msg)
+    if "yaxis2" not in fig.to_dict()["layout"]:
+        msg = "Rug y-axis should be present when show_rug is True"
+        raise AssertionError(msg)
diff --git a/uv.lock b/uv.lock
index 54b68f6f..6335acbf 100644
--- a/uv.lock
+++ b/uv.lock
@@ -6,10 +6,10 @@ resolution-markers = [
     "python_full_version >= '3.14' and sys_platform == 'emscripten'",
     "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
     "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'win32'",
-    "python_full_version < '3.12' and sys_platform == 'win32'",
     "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'emscripten'",
-    "python_full_version < '3.12' and sys_platform == 'emscripten'",
     "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'emscripten'",
     "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
 ]
 
@@ -24,64 +24,87 @@ wheels = [
 
 [[package]]
 name = "annotated-types"
-version = "0.7.0"
+version = "0.8.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
+    { url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
 ]
 
 [[package]]
 name = "anyio"
-version = "4.14.0"
+version = "4.14.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "idna" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/1c/b5/001890774a9552aff22502b8da382593109ce0c95314abaebbb116567545/anyio-4.14.0.tar.gz", hash = "sha256:b47c1f9ccf73e67021df785332508f99379c68fa7d0684e8e3492cb1d4b23f89", size = 253586, upload-time = "2026-06-15T22:00:49.021Z" }
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@@ -809,7 +942,8 @@ source = { editable = "." }
 dependencies = [
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     { name = "holidays" },
-    { name = "numpy" },
+    { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
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     { name = "openpyxl" },
     { name = "pandas" },
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@@ -817,7 +951,8 @@ dependencies = [
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     { name = "scikit-learn" },
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     { name = "pytest-xdist" },
     { name = "ruff" },
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From a28a0102d3ad1ec4d11638785a670e8fe0f4cdf7 Mon Sep 17 00:00:00 2001
From: Martin H Karrin <martin.h.karrin@captor.se>
Date: Thu, 27 Aug 2026 00:04:35 +0200
Subject: [PATCH 2/4] New version 2.1.10

---
 .pre-commit-config.yaml                  |  12 +-
 docs/README.md                           |  11 +-
 docs/requirements.txt                    |   2 +-
 docs/source/development/contributing.rst |  22 +-
 docs/source/user_guide/installation.rst  |  47 +--
 openseries/__init__.py                   |   2 +-
 openseries/portfoliotools.py             |   1 -
 pyproject.toml                           |   8 +-
 tests/test_version_alignment.py          | 443 +++++++++++++++++++++++
 uv.lock                                  |   4 +-
 10 files changed, 496 insertions(+), 56 deletions(-)
 create mode 100644 tests/test_version_alignment.py

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 88ec0fb5..3b49afa2 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -23,12 +23,12 @@ repos:
           - --non-interactive
           - --config-file=pyproject.toml
         additional_dependencies:
-          - pandas-stubs
-          - pydantic
-          - scipy-stubs
-          - types-openpyxl
-          - types-python-dateutil
-          - types-requests
+          - pandas-stubs>=2.1.2
+          - pydantic>=2.5.2
+          - scipy-stubs>=1.14.1.0
+          - types-openpyxl>=3.1.2
+          - types-python-dateutil>=2.8.2
+          - types-requests>=2.20.0
   - repo: https://github.com/pre-commit/pygrep-hooks
     rev: v1.10.0
     hooks:
diff --git a/docs/README.md b/docs/README.md
index 9c35f030..1a3bfb20 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -6,12 +6,15 @@ This directory contains the documentation for the openseries project, built usin
 
 ### Prerequisites
 
-Install the documentation dependencies using uv:
+From the repository root, install the documentation dependencies from the
+lockfile (requires the pinned uv version used in `Makefile` / CI):
 
 ```bash
-uv pip install -e ".[docs]"
+uv sync --locked --extra docs
 ```
 
+Alternatively, `make install` installs the `dev` and `docs` extras together.
+
 ### Building HTML Documentation
 
 To build the HTML documentation:
@@ -192,8 +195,8 @@ When contributing to documentation:
 
 **Missing modules:**
 
-- Install missing dependencies: `uv pip install -e ".[docs]"`
-- For ReadTheDocs builds, dependencies are managed through `pyproject.toml`
+- Install missing dependencies: `uv sync --locked --extra docs`
+- For ReadTheDocs builds, `docs/requirements.txt` must match the `docs` extra in `pyproject.toml`
 
 **Broken links:**
 
diff --git a/docs/requirements.txt b/docs/requirements.txt
index a47d4595..64fc5dea 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,4 +1,4 @@
 sphinx>=9.0.4
 sphinx-autobuild>=2025.8.25
 sphinx-autodoc-typehints>=3.6.0
-sphinx-rtd-theme>=3.1.0rc1
+sphinx-rtd-theme>=3.1.0
diff --git a/docs/source/development/contributing.rst b/docs/source/development/contributing.rst
index b5931a2b..cfb3b523 100644
--- a/docs/source/development/contributing.rst
+++ b/docs/source/development/contributing.rst
@@ -17,25 +17,19 @@ Development Setup
    git clone https://github.com/yourusername/openseries.git
    cd openseries
 
-3. Install uv (if not already installed):
+3. Create the development environment. This installs the pinned uv version
+   (``uv==0.11.21``), syncs locked ``dev`` and ``docs`` dependencies from
+   ``uv.lock``, and installs pre-commit hooks:
 
 .. code-block:: bash
 
-   pip install uv
+   make install
 
-4. Create a virtual environment and install dependencies:
+On Windows:
 
-.. code-block:: bash
-
-   uv venv venv
-   source venv/bin/activate
-   uv pip install -e ".[dev,docs]"
-
-5. Install pre-commit hooks:
-
-.. code-block:: bash
+.. code-block:: powershell
 
-   pre-commit install
+   .\make.ps1 make
 
 Development Workflow
 ~~~~~~~~~~~~~~~~~~~~
@@ -377,7 +371,7 @@ Recommended settings in ``.vscode/settings.json``:
 .. code-block:: json
 
    {
-       "python.defaultInterpreterPath": ".venv/bin/python",
+       "python.defaultInterpreterPath": "venv/bin/python",
        "python.linting.enabled": true,
        "python.linting.ruffEnabled": true,
        "python.formatting.provider": "ruff",
diff --git a/docs/source/user_guide/installation.rst b/docs/source/user_guide/installation.rst
index 3ae5fc99..69f66f93 100644
--- a/docs/source/user_guide/installation.rst
+++ b/docs/source/user_guide/installation.rst
@@ -49,25 +49,26 @@ openseries automatically installs the following dependencies:
 Core Dependencies
 ~~~~~~~~~~~~~~~~~
 
-- **pandas** (>=2.1.2,<3.0.0) - Data manipulation and analysis
-- **numpy** (>=1.23.2,!=2.3.0,<3.0.0) - Numerical computing
-- **pydantic** (>=2.5.2,<3.0.0) - Data validation and settings management
+- **pandas** (>=2.1.2) - Data manipulation and analysis
+- **numpy** (>=1.23.2) - Numerical computing
+- **pydantic** (>=2.5.2) - Data validation and settings management
 - **plotly** (>=5.18.0) - Interactive plotting
-- **scipy** (>=1.11.4,<2.0.0) - Scientific computing
-- **scikit-learn** (>=1.4.0,<2.0.0) - Machine learning utilities
+- **scipy** (>=1.14.1) - Scientific computing
+- **scikit-learn** (>=1.4.0) - Machine learning utilities
 
 Financial and Date Utilities
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-- **exchange-calendars** (>=4.8,<6.0) - Trading calendar support
-- **holidays** (>=0.30,<1.0) - Holiday calendar support
-- **python-dateutil** (>=2.8.2,<4.0.0) - Date parsing utilities
+- **exchange-calendars** (>=4.8) - Trading calendar support
+- **holidays** (>=0.30) - Holiday calendar support
+- **python-dateutil** (>=2.8.2) - Date parsing utilities
+- **tzdata** (>=2025.3) - IANA time zone data
 
 File and Network Support
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
-- **openpyxl** (>=3.1.2,<5.0.0) - Excel file support
-- **requests** (>=2.20.0,<3.0.0) - HTTP library
+- **openpyxl** (>=3.1.2) - Excel file support
+- **requests** (>=2.20.0) - HTTP library
 
 Optional Dependencies
 ~~~~~~~~~~~~~~~~~~~~~
@@ -117,27 +118,27 @@ You can also run a quick test:
 Development Installation
 ------------------------
 
-If you plan to contribute to openseries or need the development dependencies:
+If you plan to contribute to openseries or need the development dependencies,
+use the same pinned tooling as CI (``uv==0.11.21``):
 
 .. code-block:: bash
 
    git clone https://github.com/CaptorAB/openseries.git
    cd openseries
+   make install
 
-   # Install uv (if not already installed)
-   pip install uv
+On Windows, run ``.\make.ps1 make`` instead of ``make install``.
 
-   # Create a virtual environment and install dependencies
-   uv venv venv
-   source venv/bin/activate
-   uv pip install -e ".[dev]"
+This creates ``venv``, installs locked runtime, development, and documentation
+dependencies from ``uv.lock``, and installs pre-commit hooks. Development
+dependencies include:
 
-This will install additional development dependencies including:
-
-- **pytest** - Testing framework
-- **mypy** - Static type checking
-- **ruff** - Linting and formatting
-- **pre-commit** - Git hooks for code quality
+- **pytest** (>=9.1.0) - Testing framework
+- **pytest-cov** (>=7.1.0) - Coverage plugin
+- **pytest-xdist** (>=3.8.0) - Parallel test runner
+- **mypy** (==2.1.0) - Static type checking
+- **ruff** (==0.15.18) - Linting and formatting
+- **pre-commit** (>=4.6.0) - Git hooks for code quality
 
 Troubleshooting
 ---------------
diff --git a/openseries/__init__.py b/openseries/__init__.py
index 817ee99d..dec237eb 100644
--- a/openseries/__init__.py
+++ b/openseries/__init__.py
@@ -1,6 +1,6 @@
 """openseries package initialization."""
 
-__version__ = "2.1.9"
+__version__ = "2.1.10"
 
 from .datefixer import (
     date_fix,
diff --git a/openseries/portfoliotools.py b/openseries/portfoliotools.py
index 41b862ec..f42d3d5a 100644
--- a/openseries/portfoliotools.py
+++ b/openseries/portfoliotools.py
@@ -791,7 +791,6 @@ def _generate_sharpeplot_output(
             filename=str(plotfile),
             auto_open=auto_open,
             auto_play=False,
-            link_text="",
             include_plotlyjs=include_plotlyjs,
             config=fig["config"],
             output_type=output_type,
diff --git a/pyproject.toml b/pyproject.toml
index 42ec189f..e41dea98 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "openseries"
-version = "2.1.9"
+version = "2.1.10"
 description = "Tools for analyzing financial timeseries."
 authors = [
     { name = "Martin Karrin" },
@@ -51,7 +51,7 @@ dependencies = [
     "requests>=2.20.0",
     "scipy>=1.14.1",
     "scikit-learn>=1.4.0",
-    "tzdata (>=2025.3)"
+    "tzdata>=2025.3",
 ]
 
 [project.urls]
@@ -79,7 +79,7 @@ docs = [
     "sphinx>=9.0.4",
     "sphinx-autobuild>=2025.8.25",
     "sphinx-autodoc-typehints>=3.6.0",
-    "sphinx-rtd-theme>=3.1.0rc1",
+    "sphinx-rtd-theme>=3.1.0",
 ]
 
 [build-system]
@@ -97,7 +97,7 @@ openseries = [
 ]
 
 [tool.mypy]
-python_version = "3.11"
+python_version = "3.12"
 mypy_path = ["."]
 cache_dir = ".mypy_cache"
 exclude = ["venv/*", "docs/*"]
diff --git a/tests/test_version_alignment.py b/tests/test_version_alignment.py
new file mode 100644
index 00000000..c68574cc
--- /dev/null
+++ b/tests/test_version_alignment.py
@@ -0,0 +1,443 @@
+"""Test that tool and dependency versions stay aligned across config files."""
+
+from __future__ import annotations
+
+import re
+import tomllib
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).parent.parent
+PYPROJECT_PATH = ROOT / "pyproject.toml"
+LOCK_PATH = ROOT / "uv.lock"
+PRE_COMMIT_PATH = ROOT / ".pre-commit-config.yaml"
+MAKEFILE_PATH = ROOT / "Makefile"
+MAKE_PS1_PATH = ROOT / "make.ps1"
+DOCS_REQUIREMENTS_PATH = ROOT / "docs" / "requirements.txt"
+INSTALLATION_RST_PATH = ROOT / "docs" / "source" / "user_guide" / "installation.rst"
+CONTRIBUTING_RST_PATH = ROOT / "docs" / "source" / "development" / "contributing.rst"
+PYTHON_VERSION_PATH = ROOT / ".python-version"
+ZIZMOR_SCRIPT_PATH = ROOT / "scripts" / "run-zizmor.sh"
+WORKFLOW_DIR = ROOT / ".github" / "workflows"
+
+UV_WORKFLOW_FILES = (
+    "test.yml",
+    "build.yml",
+    "docs.yml",
+    "deploy.yml",
+    "codeql.yml",
+    "zizmor.yml",
+    "supply-chain.yml",
+)
+
+MYPY_ADDITIONAL_DEPENDENCIES = (
+    "pandas-stubs",
+    "pydantic",
+    "scipy-stubs",
+    "types-openpyxl",
+    "types-python-dateutil",
+    "types-requests",
+)
+
+
+class VersionAlignmentError(Exception):
+    """Raised when a pinned version is not aligned across project files."""
+
+
+def _read_text(path: Path) -> str:
+    return path.read_text(encoding="utf-8")
+
+
+def _load_toml(path: Path) -> dict[str, Any]:
+    with path.open("rb") as handle:
+        return tomllib.load(handle)
+
+
+def _requirement_parts(requirement: str) -> tuple[str, str]:
+    compact = requirement.strip().replace(" ", "")
+    for separator in ("==", ">="):
+        if separator in compact:
+            name, spec = compact.split(separator, 1)
+            return name, f"{separator}{spec}"
+    msg = f"Unsupported requirement specifier: {requirement}"
+    raise VersionAlignmentError(msg)
+
+
+def _requirement_map(requirements: list[str]) -> dict[str, str]:
+    return dict(_requirement_parts(item) for item in requirements)
+
+
+def _makefile_value(text: str, name: str) -> str:
+    match = re.search(rf"^{name} \?= (.+)$", text, flags=re.MULTILINE)
+    if match is None:
+        msg = f"{MAKEFILE_PATH.name} is missing {name}"
+        raise VersionAlignmentError(msg)
+    return match.group(1).strip()
+
+
+def _ps1_value(text: str, name: str) -> str:
+    match = re.search(rf'\${name} = "([^"]+)"', text)
+    if match is None:
+        msg = f"{MAKE_PS1_PATH.name} is missing {name}"
+        raise VersionAlignmentError(msg)
+    return match.group(1)
+
+
+def _workflow_env_value(text: str, name: str) -> str:
+    match = re.search(rf"^\s*{name}: \"([^\"]+)\"", text, flags=re.MULTILINE)
+    if match is None:
+        msg = f"Workflow is missing {name}"
+        raise VersionAlignmentError(msg)
+    return match.group(1)
+
+
+def _pre_commit_rev(text: str, repo_url: str) -> str:
+    pattern = rf"repo: {re.escape(repo_url)}\n\s+rev: (.+)"
+    match = re.search(pattern, text)
+    if match is None:
+        msg = f"{PRE_COMMIT_PATH.name} is missing rev for {repo_url}"
+        raise VersionAlignmentError(msg)
+    return match.group(1).strip()
+
+
+def _pre_commit_additional_dependencies(text: str) -> dict[str, str]:
+    match = re.search(
+        r"additional_dependencies:\n((?:          - .+\n)+)",
+        text,
+    )
+    if match is None:
+        msg = f"{PRE_COMMIT_PATH.name} is missing mypy additional_dependencies"
+        raise VersionAlignmentError(msg)
+    requirements = [
+        line.strip()[2:].strip()
+        for line in match.group(1).splitlines()
+        if line.strip().startswith("- ")
+    ]
+    return _requirement_map(requirements)
+
+
+def _lock_requires_dist(
+    lock_data: dict[str, Any],
+) -> dict[tuple[str, str | None], str]:
+    packages = lock_data.get("package", [])
+    for package in packages:
+        if package.get("name") != "openseries":
+            continue
+        metadata = package.get("metadata", {})
+        requires_dist = metadata.get("requires-dist", [])
+        mapped: dict[tuple[str, str | None], str] = {}
+        for item in requires_dist:
+            extra = None
+            marker = item.get("marker")
+            if marker is not None:
+                extra_match = re.search(r"extra == '([^']+)'", marker)
+                if extra_match is not None:
+                    extra = extra_match.group(1)
+            mapped[(item["name"], extra)] = item["specifier"]
+        return mapped
+    msg = "uv.lock is missing the openseries package metadata"
+    raise VersionAlignmentError(msg)
+
+
+def _python_minor_versions(requires_python: str) -> list[str]:
+    match = re.fullmatch(r">=(\d+\.\d+),<(\d+\.\d+)", requires_python.replace(" ", ""))
+    if match is None:
+        msg = f"Unexpected requires-python: {requires_python}"
+        raise VersionAlignmentError(msg)
+    start_major, start_minor = (int(part) for part in match.group(1).split("."))
+    end_major, end_minor = (int(part) for part in match.group(2).split("."))
+    if start_major != end_major:
+        msg = f"requires-python spans multiple majors: {requires_python}"
+        raise VersionAlignmentError(msg)
+    return [f"{start_major}.{minor}" for minor in range(start_minor, end_minor)]
+
+
+def _raise_mismatch(label: str, expected: str, actual: str) -> None:
+    msg = f"{label} is {actual!r}, expected {expected!r}"
+    raise VersionAlignmentError(msg)
+
+
+def _required_search(pattern: str, text: str, label: str) -> re.Match[str]:
+    match = re.search(pattern, text, flags=re.MULTILINE)
+    if match is None:
+        msg = f"{label} is missing"
+        raise VersionAlignmentError(msg)
+    return match
+
+
+def _check_python_classifiers(classifiers: list[str], versions: list[str]) -> None:
+    for version in versions:
+        expected = f"Programming Language :: Python :: {version}"
+        if expected not in classifiers:
+            msg = f"pyproject.toml classifiers are missing {expected}"
+            raise VersionAlignmentError(msg)
+
+
+def _check_default_python_pins(python_version: str) -> None:
+    actual_default = _read_text(PYTHON_VERSION_PATH).strip()
+    if actual_default != python_version:
+        _raise_mismatch(".python-version", python_version, actual_default)
+    language_match = _required_search(
+        r"^  python: python(.+)$",
+        _read_text(PRE_COMMIT_PATH),
+        "pre-commit default_language_version",
+    )
+    if language_match.group(1) != python_version:
+        _raise_mismatch(
+            "pre-commit python",
+            python_version,
+            language_match.group(1),
+        )
+    rtd_match = _required_search(
+        r'^    python: "([^"]+)"$',
+        _read_text(ROOT / ".readthedocs.yaml"),
+        ".readthedocs.yaml python version",
+    )
+    if rtd_match.group(1) != python_version:
+        _raise_mismatch(".readthedocs.yaml python", python_version, rtd_match.group(1))
+
+
+def _check_python_matrix_and_docs(versions: list[str]) -> None:
+    matrix_match = _required_search(
+        r"python-version: \[ ([^\]]+) \]",
+        _read_text(WORKFLOW_DIR / "build.yml"),
+        "build.yml python-version matrix",
+    )
+    matrix_versions = [
+        item.strip().strip("'\"") for item in matrix_match.group(1).split(",")
+    ]
+    if matrix_versions != versions:
+        _raise_mismatch(
+            "build.yml python-version matrix",
+            ", ".join(versions),
+            ", ".join(matrix_versions),
+        )
+    listed = ", ".join(versions)
+    if listed not in _read_text(INSTALLATION_RST_PATH):
+        msg = f"{INSTALLATION_RST_PATH.name} is missing Python versions {listed}"
+        raise VersionAlignmentError(msg)
+
+
+def _check_type_checker_targets(
+    pyproject: dict[str, Any],
+    versions: list[str],
+) -> None:
+    mypy_version = pyproject["tool"]["mypy"]["python_version"]
+    if mypy_version not in versions:
+        msg = (
+            "tool.mypy python_version must be a supported Python version, "
+            f"got {mypy_version!r}"
+        )
+        raise VersionAlignmentError(msg)
+    ruff_target = pyproject["tool"]["ruff"]["target-version"]
+    expected_ruff_target = f"py{versions[0].replace('.', '')}"
+    if ruff_target != expected_ruff_target:
+        _raise_mismatch("tool.ruff target-version", expected_ruff_target, ruff_target)
+
+
+class TestVersionAlignment:
+    """class to verify dependency and tool versions stay aligned."""
+
+    def test_lockfile_matches_pyproject(self: TestVersionAlignment) -> None:
+        """Test uv.lock metadata matches pyproject.toml specifiers."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        lock_requires = _lock_requires_dist(_load_toml(LOCK_PATH))
+        expected: dict[tuple[str, str | None], str] = {}
+        for requirement in pyproject["project"]["dependencies"]:
+            name, specifier = _requirement_parts(requirement)
+            expected[(name, None)] = specifier
+        extras = pyproject["project"]["optional-dependencies"]
+        for extra, requirements in extras.items():
+            for requirement in requirements:
+                name, specifier = _requirement_parts(requirement)
+                expected[(name, extra)] = specifier
+        if lock_requires != expected:
+            msg = (
+                "uv.lock package metadata does not match pyproject.toml: "
+                f"{lock_requires} != {expected}"
+            )
+            raise VersionAlignmentError(msg)
+
+    def test_docs_requirements_match_docs_extra(self: TestVersionAlignment) -> None:
+        """Test docs/requirements.txt matches the pyproject docs extra."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        expected = [
+            item.replace(" ", "")
+            for item in pyproject["project"]["optional-dependencies"]["docs"]
+        ]
+        actual = [
+            line.strip().replace(" ", "")
+            for line in _read_text(DOCS_REQUIREMENTS_PATH).splitlines()
+            if line.strip() and not line.strip().startswith("#")
+        ]
+        if actual != expected:
+            msg = (
+                "docs/requirements.txt does not match pyproject docs extra: "
+                f"{actual} != {expected}"
+            )
+            raise VersionAlignmentError(msg)
+
+    def test_tool_versions_match(self: TestVersionAlignment) -> None:
+        """Test uv, ruff, and mypy versions match across tooling files."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        dev_requirements = _requirement_map(
+            pyproject["project"]["optional-dependencies"]["dev"],
+        )
+        pre_commit = _read_text(PRE_COMMIT_PATH)
+        makefile = _read_text(MAKEFILE_PATH)
+        make_ps1 = _read_text(MAKE_PS1_PATH)
+
+        uv_version = _makefile_value(makefile, "UV_VERSION")
+        if _ps1_value(make_ps1, "UV_VERSION") != uv_version:
+            _raise_mismatch(
+                "make.ps1 UV_VERSION",
+                uv_version,
+                _ps1_value(make_ps1, "UV_VERSION"),
+            )
+        uv_rev = _pre_commit_rev(
+            pre_commit,
+            "https://github.com/astral-sh/uv-pre-commit",
+        )
+        if uv_rev != uv_version:
+            _raise_mismatch("pre-commit uv rev", uv_version, uv_rev)
+
+        ruff_spec = dev_requirements["ruff"]
+        if not ruff_spec.startswith("=="):
+            msg = f"ruff must be pinned exactly in pyproject.toml, got {ruff_spec}"
+            raise VersionAlignmentError(msg)
+        ruff_version = ruff_spec[2:]
+        ruff_rev = _pre_commit_rev(
+            pre_commit,
+            "https://github.com/astral-sh/ruff-pre-commit",
+        )
+        if ruff_rev != f"v{ruff_version}":
+            _raise_mismatch("pre-commit ruff rev", f"v{ruff_version}", ruff_rev)
+
+        mypy_spec = dev_requirements["mypy"]
+        if not mypy_spec.startswith("=="):
+            msg = f"mypy must be pinned exactly in pyproject.toml, got {mypy_spec}"
+            raise VersionAlignmentError(msg)
+        mypy_version = mypy_spec[2:]
+        mypy_rev = _pre_commit_rev(
+            pre_commit,
+            "https://github.com/pre-commit/mirrors-mypy",
+        )
+        if mypy_rev != f"v{mypy_version}":
+            _raise_mismatch("pre-commit mypy rev", f"v{mypy_version}", mypy_rev)
+
+        for workflow_name in UV_WORKFLOW_FILES:
+            workflow_text = _read_text(WORKFLOW_DIR / workflow_name)
+            actual = _workflow_env_value(workflow_text, "UV_VERSION")
+            if actual != uv_version:
+                _raise_mismatch(
+                    f"{workflow_name} UV_VERSION",
+                    uv_version,
+                    actual,
+                )
+
+    def test_audit_and_zizmor_versions_match(self: TestVersionAlignment) -> None:
+        """Test pip-audit and zizmor versions match across scripts and CI."""
+        makefile = _read_text(MAKEFILE_PATH)
+        make_ps1 = _read_text(MAKE_PS1_PATH)
+        pip_audit_version = _makefile_value(makefile, "PIP_AUDIT_VERSION")
+        if _ps1_value(make_ps1, "PIP_AUDIT_VERSION") != pip_audit_version:
+            _raise_mismatch(
+                "make.ps1 PIP_AUDIT_VERSION",
+                pip_audit_version,
+                _ps1_value(make_ps1, "PIP_AUDIT_VERSION"),
+            )
+        supply_chain = _read_text(WORKFLOW_DIR / "supply-chain.yml")
+        actual_pip_audit = _workflow_env_value(supply_chain, "PIP_AUDIT_VERSION")
+        if actual_pip_audit != pip_audit_version:
+            _raise_mismatch(
+                "supply-chain.yml PIP_AUDIT_VERSION",
+                pip_audit_version,
+                actual_pip_audit,
+            )
+
+        zizmor_workflow = _read_text(WORKFLOW_DIR / "zizmor.yml")
+        zizmor_version = _workflow_env_value(zizmor_workflow, "ZIZMOR_VERSION")
+        script_match = re.search(
+            r"^readonly ZIZMOR_VERSION=(.+)$",
+            _read_text(ZIZMOR_SCRIPT_PATH),
+            flags=re.MULTILINE,
+        )
+        if script_match is None:
+            msg = "scripts/run-zizmor.sh is missing ZIZMOR_VERSION"
+            raise VersionAlignmentError(msg)
+        if script_match.group(1) != zizmor_version:
+            _raise_mismatch(
+                "scripts/run-zizmor.sh ZIZMOR_VERSION",
+                zizmor_version,
+                script_match.group(1),
+            )
+
+    def test_mypy_additional_dependencies_match_pyproject(
+        self: TestVersionAlignment,
+    ) -> None:
+        """Test pre-commit mypy extra deps match pyproject specifiers."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        declared = _requirement_map(pyproject["project"]["dependencies"])
+        declared.update(
+            _requirement_map(pyproject["project"]["optional-dependencies"]["dev"]),
+        )
+        actual = _pre_commit_additional_dependencies(_read_text(PRE_COMMIT_PATH))
+        expected = {
+            name: declared[name]
+            for name in MYPY_ADDITIONAL_DEPENDENCIES
+            if name in declared
+        }
+        if actual != expected:
+            msg = (
+                "pre-commit mypy additional_dependencies do not match "
+                f"pyproject.toml: {actual} != {expected}"
+            )
+            raise VersionAlignmentError(msg)
+
+    def test_docs_list_pyproject_specifiers(self: TestVersionAlignment) -> None:
+        """Test installation and contributing docs list current specifiers."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        installation = _read_text(INSTALLATION_RST_PATH)
+        contributing = _read_text(CONTRIBUTING_RST_PATH)
+        uv_version = _makefile_value(_read_text(MAKEFILE_PATH), "UV_VERSION")
+
+        runtime = _requirement_map(pyproject["project"]["dependencies"])
+        for name, specifier in runtime.items():
+            expected = f"**{name}** ({specifier})"
+            if expected not in installation:
+                msg = f"{INSTALLATION_RST_PATH.name} is missing {expected}"
+                raise VersionAlignmentError(msg)
+
+        dev = _requirement_map(pyproject["project"]["optional-dependencies"]["dev"])
+        documented_dev = (
+            "pytest",
+            "pytest-cov",
+            "pytest-xdist",
+            "mypy",
+            "ruff",
+            "pre-commit",
+        )
+        for name in documented_dev:
+            expected = f"**{name}** ({dev[name]})"
+            if expected not in installation:
+                msg = f"{INSTALLATION_RST_PATH.name} is missing {expected}"
+                raise VersionAlignmentError(msg)
+
+        uv_pin = f"uv=={uv_version}"
+        if uv_pin not in installation:
+            msg = f"{INSTALLATION_RST_PATH.name} is missing {uv_pin}"
+            raise VersionAlignmentError(msg)
+        if uv_pin not in contributing:
+            msg = f"{CONTRIBUTING_RST_PATH.name} is missing {uv_pin}"
+            raise VersionAlignmentError(msg)
+
+    def test_python_versions_match(self: TestVersionAlignment) -> None:
+        """Test declared Python versions match CI, docs, and tool targets."""
+        pyproject = _load_toml(PYPROJECT_PATH)
+        requires_python = pyproject["project"]["requires-python"].replace(" ", "")
+        versions = _python_minor_versions(requires_python)
+        default_version = versions[-1]
+        _check_python_classifiers(pyproject["project"]["classifiers"], versions)
+        _check_default_python_pins(default_version)
+        _check_python_matrix_and_docs(versions)
+        _check_type_checker_targets(pyproject, versions)
diff --git a/uv.lock b/uv.lock
index 6335acbf..4171ce81 100644
--- a/uv.lock
+++ b/uv.lock
@@ -937,7 +937,7 @@ wheels = [
 
 [[package]]
 name = "openseries"
-version = "2.1.9"
+version = "2.1.10"
 source = { editable = "." }
 dependencies = [
     { name = "exchange-calendars" },
@@ -1004,7 +1004,7 @@ requires-dist = [
     { name = "sphinx", marker = "extra == 'docs'", specifier = ">=9.0.4" },
     { name = "sphinx-autobuild", marker = "extra == 'docs'", specifier = ">=2025.8.25" },
     { name = "sphinx-autodoc-typehints", marker = "extra == 'docs'", specifier = ">=3.6.0" },
-    { name = "sphinx-rtd-theme", marker = "extra == 'docs'", specifier = ">=3.1.0rc1" },
+    { name = "sphinx-rtd-theme", marker = "extra == 'docs'", specifier = ">=3.1.0" },
     { name = "types-openpyxl", marker = "extra == 'dev'", specifier = ">=3.1.2" },
     { name = "types-python-dateutil", marker = "extra == 'dev'", specifier = ">=2.8.2" },
     { name = "types-requests", marker = "extra == 'dev'", specifier = ">=2.20.0" },

From 81cc787282f78491b06993dff6cadec95e642c3e Mon Sep 17 00:00:00 2001
From: Martin H Karrin <martin.h.karrin@captor.se>
Date: Fri, 28 Aug 2026 11:15:06 +0200
Subject: [PATCH 3/4] fixed build test of new version 2.1.10

---
 .github/workflows/build.yml | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 8f535c50..780d840e 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -48,6 +48,8 @@ jobs:
         uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d # v10.0.1
         with:
           version: ${{ env.UV_VERSION }}
+          python-version: ${{ matrix.python-version }}
+          cache-suffix: py${{ matrix.python-version }}
 
       - name: Sync dependencies (locked)
         run: uv sync --locked --extra dev
@@ -122,6 +124,8 @@ jobs:
         uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d # v10.0.1
         with:
           version: ${{ env.UV_VERSION }}
+          python-version: ${{ matrix.python-version }}
+          cache-suffix: py${{ matrix.python-version }}
 
       - name: Sync dependencies (locked)
         run: uv sync --locked --extra dev
@@ -196,6 +200,8 @@ jobs:
         uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d # v10.0.1
         with:
           version: ${{ env.UV_VERSION }}
+          python-version: ${{ matrix.python-version }}
+          cache-suffix: py${{ matrix.python-version }}
 
       - name: Sync dependencies (locked)
         run: uv sync --locked --extra dev

From c5a9858cee2a0338312eabc8e712483e77d5b24c Mon Sep 17 00:00:00 2001
From: Martin H Karrin <martin.h.karrin@captor.se>
Date: Fri, 28 Aug 2026 11:31:42 +0200
Subject: [PATCH 4/4] fixed test workflow ahead of new version 2.1.10

---
 .github/workflows/test.yml | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index e6c25c48..f4c77b76 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -17,9 +17,7 @@ on:
   workflow_dispatch: {}
   push:
     branches:
-      - "*"
-      - "*/*"
-      - "**"
+      - master
   pull_request:
     branches:
       - master