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Two-Sample Testing for Tail Copulas with an Application to Equity Indices

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  • Can, S.U.
  • Einmahl, John

    (Tilburg University, School of Economics and Management)

  • Laeven, Roger

Abstract

A novel, general two-sample hypothesis testing procedure is established for testing the equality of tail copulas associated with bivariate data. More precisely, using a martingale transformation of a natural two-sample tail copula process, a test process is constructed, which is shown to converge in distribution to a standard Wiener process. Hence, from this test process a myriad of asymptotically distribution-free two-sample tests can be obtained. The good finite-sample behavior of our procedure is demonstrated through Monte Carlo simulations. Using the new testing procedure, no evidence of a difference in the respective tail copulas is found for pairs of negative daily log-returns of equity indices during and after the global financial crisis.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Can, S.U. & Einmahl, John & Laeven, Roger, 2021. "Two-Sample Testing for Tail Copulas with an Application to Equity Indices," Other publications TiSEM 65a9e694-665d-4671-aaf1-4, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:65a9e694-665d-4671-aaf1-4e2093fcec17
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    References listed on IDEAS

    as
    1. Einmahl, John H.J. & de Haan, Laurens & Sinha, Ashoke Kumar, 1997. "Estimating the spectral measure of an extreme value distribution," Stochastic Processes and their Applications, Elsevier, vol. 70(2), pages 143-171, October.
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