ICLR25 | Official code base for Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models (DLPM)
Large t-Vector AutoRegressive models with volatility spillovers and networks. Code of the paper Barbaglia, Croux, Wilms (2020) "Volatility Spillovers in Commodity Markets: A Large t-Vector AutoRegressive Approach", Energy Economics.
pylambertw - sklearn interface to analyze and gaussianize heavy-tailed, skewed data
AUB's Heavy-Tails Package
GPM-GARCH: Endogenous heavy-tail formation as a bifurcation phenomenon. Early-warning system for CLT breakdown in financial markets. Formal proofs + empirical validation on 7 markets (2002–2026).
Cross-domain predictive modeling: Monte Carlo + Tails/Markov/HOMER hybrids for physics, finance, social dynamics. Implements 3 predictive pairs from arXiv paper with 2-4x FOM gains: • MoP-Tails: heavy-tail risk (finance crashes) • MCMC-HOMER: energy optimization • HMC-PDMP: physics/social cascades Live Jupyter demos • MIT License • Chicago rese
Severity modelling for insurance pricing - spliced distributions, DRN, composite regression, EQRN extreme quantiles
Implements the estimators and algorithms described in Chapters 8 and 9 of the book "The Fundamentals of Heavy Tails: Properties, Emergence, and Estimation" by Nair et al. (2022, ISBN:9781009053730), including the Hill, Moments, Pickands, and Peaks-over-Threshold (POT) estimators, Power-law fit, and the Double Bootstrap algorithm.
Add a description, image, and links to the heavy-tails topic page so that developers can more easily learn about it.
To associate your repository with the heavy-tails topic, visit your repo's landing page and select "manage topics."