fat-tails

Code and Notes for fat-tailed statistics.

Contingency Random Number Generator — numbers with controllable fat tails, volatility clustering, and scale convergence

Crash detection via fat-tail statistics. LPPLS, EVT, Hill, Kappa. Rust core + Python.

A fat-tail-native quantitative finance toolkit for Python.

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

CUDA based financial calculation suit

Five textbook distributions (Normal, Student-t, Bernoulli, Poisson, Uniform) tested as hypotheses on S&P 500 and KOSPI returns, out-of-sample.

Re-creating Fig. 19.3 from Nassim Taleb's Statistical Consequences of Fat Tails in Mathematica

This repository contains Python implementations of tables and figures from the reference textbook !Robust Statistics Theory and Methods!. The goal is to provide reproducible, executable code for visualizations and results presented in the book.

Implementation https://arxiv.org/abs/1802.05495

MQL5 volatility and fat-tail research tools for regime-aware trading systems and risk monitoring.

BSE SENSEX vs Geometric Brownian Motion (GBM) with Student-t Heavy Tails and GARCH(1,1) Volatility Clustering

Companion notebook for the post “Algo Backtests Are Lying to You.”