Code for the WSDM 2021 paper "FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection".

Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.

This project studies the effects of the shape parameter estimator uncertainty at different threshold levels on the value-at-risk confidence interval for quantitative risk management (QRM) using the Generalized Pareto Distribution (GPD) from the Extreme Value Theory (EVT) approach.

[ DPhil project ] Extreme value theory and GANs to generate compound coastal hazards (wind speed + sea level pressure) from ERA5 reanalysis data over the Bay of Bengal. In development...

Official Python implementation of the Pioneer Detection Method (PDM) — convergence-based expert aggregation and opinion pooling under structural change. Code for Vansteenberghe (2026), The Geneva Papers 51(1).

Python package for fitting statistical models using calibrating priors.

EVT-based noise injection toolkit for evaluating time series forecasting robustness

Pure-Python library of heavy-tailed probability distributions (Pareto, Burr, LogNormal, etc.) built from first principles.

Estimate tail parameters of heavy-tailed distributions (including power law exponent gamma) in Python

Potential Height Python packages: runs the experiments for "Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian optimization"

A deep study of human longevity using demographic data (HLD, IDL) and Extreme Value Theory to assess the potential existence of a theoretical limit to human lifespan

Climate-aware economic scenario generator for ORSA applications under Solvency II, with climate-adjusted tail risk modeling.

Find The Tail - Matlab

GNN for spatiotemporal Forecasting using Extreme Value Theory

Two-stage frequentist framework for fusing sparse observations with dense simulations in spatial extreme value analysis

End-to-End Python implementation of Hayward et. al's (2026) method for modeling financial volatility as a nonlinear wave system. Extracts VIX/VXO/VSTOXX envelopes via FFT and Hilbert transforms, builds a Schrödinger-type Hamiltonian, and tracks eigenvalue-gradient shifts signaling Anderson localisation ahead of volatility events. 

R package for estimation of elliptical extreme quantile regions

Multi-asset VaR & stress-testing framework: 5 VaR methods + Expected Shortfall, Kupiec/Christoffersen backtesting, GARCH-FHS, EVT, component VaR.

A specialized Python library for sparse multivariate extreme value analysis, structure learning, and robust spectral measure estimation using extremal graphical models.