student-t

Mean and Covariance Matrix Estimation under Heavy Tails

Python (pip) package for fitting mixtures of Student's t-distributions using either maximum likelihood (EM) or Bayesian methodology (variational mean-field)

A python implementation of the skewed student-t distribution

RL skeleton codebase with Hydra configs, Slurm/submitit, and MySQL/MariaDB logging.

Record a sample and compute its statistical significance.

Code for reproducing the results in arXiv:2109.01726

Statistical analysis of fat tails, volatility clustering, and VaR underestimation in AAPL & TSLA returns — arXiv forthcoming

Statistical analysis of fat-tailed return distributions in NSE50 Indian equity markets: GARCH filtering, Student-t MLE, VaR comparison, and Misspecification Tax

An R package for time series modelling with mixture autoregressive and related models.

Fit Student-t distribution to univariate data in Fortran and Python with SciPy and compare speed

Simple pyhton package for caluclating random uncertanity of a set of repeted measurments.

Multi-asset market risk engine in Python for VaR, Expected Shortfall, backtesting, stress testing, and model validation.