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A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance

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  • Žikica Lukić

    (University of Belgrade)

  • Bojana Milošević

    (University of Belgrade)

Abstract

This paper introduces a novel two-sample test for a broad class of orthogonally invariant positive definite symmetric matrix distributions. Our test is the first of its kind, and we derive its asymptotic distribution. To estimate the test power, we use a warp-speed bootstrap method and consider the most common matrix distributions. We provide several real data examples, including the data for main cryptocurrencies and stock data of major US companies. The real data examples demonstrate the applicability of our test in the context closely related to algorithmic trading. The popularity of matrix distributions in many applications and the need for such a test in the literature are reconciled by our findings.

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  • Žikica Lukić & Bojana Milošević, 2024. "A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(5), pages 797-820, October.
    • Handle: RePEc:spr:aistmt:v:76:y:2024:i:5:d:10.1007_s10463-024-00902-z
    DOI: 10.1007/s10463-024-00902-z
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    References listed on IDEAS

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    Cited by:

    1. Žikica Lukić & Bojana Milošević, 2024. "Change-point analysis for matrix data: the empirical Hankel transform approach," Statistical Papers, Springer, vol. 65(9), pages 5955-5980, December.

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