Extracting the "dot plot" economic projections posted online by the Federal Open Market Committee
Real-time macroeconomic & financial markets dashboard featuring AI sentiment analysis , Fed Funds backtesting, and live multi-asset tracking
End-to-End Python implementation of "FedSight AI" multi-agent system for Federal Funds Target Rate prediction (NeurIPS 2025 Workshop). Simulates FOMC deliberations using LLMs with Chain-of-Draft reasoning and In-Context Learning. Integrates structured macro indicators with unstructured narratives (Beige Book, Dot Plots).
Open macro-cycle observatory for current regimes, long-wave history, official macro release ledgers, watchlists, and evidence-gated readings.
Agentic RAG system using LangGraph to analyse FOMC documents, detect monetary policy shifts, and identify contradictions across Federal Reserve meetings. Built with Pinecone, GPT-4o, FastAPI, and evaluated with RAGAS.
A command-line tool for analyzing Federal Reserve policy scenarios by finding historical analogues based on unemployment and inflation conditions.
Fully automated macro calendar — FOMC, BOE, ECB, BOJ, US CPI/PPI/NFP in Google Calendar. Completely free (no paid APIs).
Personal monitor of Federal Reserve communications: scrapes Board governor speeches and FOMC docs, scores hawk/dove tone via Claude, alerts on tone shifts.
Projet de NLP appliqué aux conférences de presse du FOMC (2020–2025) visant à analyser l’évolution du discours monétaire de la Réserve fédérale américaine. À travers des méthodes de text mining, TF-IDF, clustering et analyse de sentiments, le projet étudie les thèmes macroéconomiques dominants et leurs corrélations avec les marchés financiers.
美联储主席 Kevin Warsh 首场 FOMC 新闻发布会（2026 年 6 月 17 日）完整中英双语逐字稿。非官方，本地转录整理。
This repository automatically scrapes the past and future FOMC meeting statements & minutes - tracking US monetary policy changes through time.
Leakage-free real-time evaluation of open-weights LLMs for US CPI inflation forecasting. Introduces the memorization premium (seen vs. unseen forecast-error gap) and a three-role decomposition (direct forecaster, FOMC-text extractor, combiner). Reproduces every number in the IJF manuscript's Table 3 from the committed checkpoint.
Empirical macro-finance project on FOMC statement entropy and post-meeting VIX reactions
Full-stack ML project predicting US Treasury yield moves after FOMC meetings: DistilBERT sentiment + macro regime classification + walk-forward gradient boosting, with a Next.js dashboard
Study of the impact of monetary policy and central bank sentiment on gold price dynamics. Built a dataset combining quantitative market variables and qualitative FOMC-statement features, then evaluated predictive power through rolling Ridge regression and GARCH models.
Undergraduate thesis: measuring non-verbal cues in FOMC press conferences and testing them against high-frequency futures reactions.
FOMC sentiment resources linked to FinBERT aspect classification model
A multimodal RAG pipeline for complex financial analysis, combining vision-based table extraction (Qwen2-VL) with hybrid retrieval and code-driven visualization.
AI market research dashboard with FOMC RAG, hybrid search, citations, and evaluation
Output Federal Reserve FOMC Meeting Dates in a plain text ISO date format for further use elsewhere
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