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Adaptive Testing for Alphas in High-Dimensional Factor Pricing Models

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  • Qiang Xia
  • Xianyang Zhang

Abstract

This article proposes a new procedure to validate the multi-factor pricing theory by testing the presence of alpha in linear factor pricing models with a large number of assets. Because the market’s inefficient pricing is likely to occur to a small fraction of exceptional assets, we develop a testing procedure that is particularly powerful against sparse signals. Based on the high-dimensional Gaussian approximation theory, we propose a simulation-based approach to approximate the limiting null distribution of the test. Our numerical studies show that the new procedure can deliver a reasonable size and achieve substantial power improvement compared to the existing tests under sparse alternatives, and especially for weak signals.

Suggested Citation

  • Qiang Xia & Xianyang Zhang, 2024. "Adaptive Testing for Alphas in High-Dimensional Factor Pricing Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 640-653, April.
  • Handle: RePEc:taf:jnlbes:v:42:y:2024:i:2:p:640-653
    DOI: 10.1080/07350015.2023.2217871
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