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arXiv · 2410.02918

Moving sum procedure for multiple change point detection in large factor models

Matteo Barigozzi·Haeran Cho·Lorenzo Trapani
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Abstract

This paper proposes a moving sum methodology for detecting multiple change points in high-dimensional time series under a factor model, where changes are attributed to those in loadings as well as emergence or disappearance of factors. We establish the asymptotic null distribution of the proposed test for family-wise error control, and show the consistency of the procedure for multiple change point estimation. Simulation studies and an application to a large dataset of volatilities demonstrate the competitive performance of the proposed method.

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Matteo Barigozzi, Haeran Cho, Lorenzo Trapani. 2024-10-03. Moving sum procedure for multiple change point detection in large factor models. https://arxiv.org/abs/2410.02918

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