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Permutation test of tail dependence

Author

Listed:
  • Bojan Basrak

    (University of Zagreb, Faculty of Science)

  • Darko Brborović

    (University of Zagreb, Faculty of Science)

Abstract

We propose and analyze a permutation test of the tail dependence between two random variables whose marginal distributions are assumed to be known. Justifying the test, we show that the proposed test statistics and their permutation distribution converge to the normal distribution. The analysis is motivated by the recent results of DiCiccio and Romano (J Am Stat Assoc 112(519):1211–1220, 2017) on permutation tests for correlation between random variables. We also provide a simulation study of the size and power properties of the test and an application to financial data.

Suggested Citation

  • Bojan Basrak & Darko Brborović, 2024. "Permutation test of tail dependence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(1), pages 89-129, March.
    • Handle: RePEc:spr:stmapp:v:33:y:2024:i:1:d:10.1007_s10260-023-00723-z
    DOI: 10.1007/s10260-023-00723-z
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    References listed on IDEAS

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    4. Hofert, Marius & Maechler, Martin, 2011. "Nested Archimedean Copulas Meet R: The nacopula Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i09).
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    8. Cyrus J. DiCiccio & Joseph P. Romano, 2017. "Robust Permutation Tests For Correlation And Regression Coefficients," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1211-1220, July.
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