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

Sami Umut Can, John H. J. Einmahl and Roger Laeven

Journal of Business & Economic Statistics, 2024, vol. 42, issue 1, 147-159

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.

Date: 2024
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Working Paper: Two-Sample Testing for Tail Copulas with an Application to Equity Indices (2021)
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DOI: 10.1080/07350015.2023.2166050

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