A Stepwise Cauchy Combination Test for Multiple Testing Problems with Financial Applications

Nabil Bouamara, Sébastien Laurent () and Shuping Shi
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Nabil Bouamara: LIDAM - Louvain Institute of Data Analysis and Modeling in economics and statistics
Sébastien Laurent: AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, Aix-Marseille Graduate School of Management
Shuping Shi: Macquarie University [Sydney]

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Abstract: We propose the stepwise Cauchy combination test (StepC), a new procedure for multiple testing with dependent test statistics and sparse signals. Unlike the global version, StepC pinpoints which p-values drive rejections, while maintaining strong familywise error control. It is less conservative under dependence and more powerful than conventional multiple testing corrections. In simulations and in applications to drift burst detection and testing for nonzero alphas, StepC consistently boosts power and yields more meaningful rejections, making it a practical alternative for large-scale financial datasets.

Keywords: nonasymptotic approximation; sequential rejection; multiple hypothesis testing; familywise error; dependence (search for similar items in EconPapers)
Date: 2025-09-18
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Published in Journal of Financial Econometrics, 2025, 23 (5), ⟨10.1093/jjfinec/nbaf020⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05443865

DOI: 10.1093/jjfinec/nbaf020

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