structural-breaks

25 structural break detection methods for univariate time series: XGBoost, Neural Networks, Ensembles, Reinforcement Learning, and Statistical approaches. Evaluated on cross-dataset generalization.

Fundamental package for quantitative finance with Python.

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).

Bai–Perron structural break detection and estimation for time series and panel data. Tests for breaks, estimates break dates with confidence intervals, and selects break counts via sequential testing or information criteria.

Loss cost trend analysis for insurance pricing — frequency/severity decomposition, ONS index integration, structural break detection (154 tests)

Replication Files and Notes for: Level Breaks and Finite-Sample GLS Detrending: The Point-Optimal Unit Root Test and the Purchasing Power Parity Puzzle

A reproducible time-series case study on regime instability and forecast failure in U.S. trade-balance forecasting.

Quantify SHAP feature importance stability across structural breaks in time-series data