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Dependence on Tail Copula

Author

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  • Paramahansa Pramanik

    (Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36608, USA)

Abstract

In real-world scenarios, we encounter non-exchangeable dependence structures. Our primary focus is on identifying and quantifying non-exchangeability in the tails of joint distributions. The findings and methodologies presented in this study are particularly valuable for modeling bivariate dependence, especially in fields where understanding dependence patterns in the tails is crucial, such as quantitative finance, quantitative risk management, and econometrics. To grasp the intricate relationship between the strength of dependence and various types of margins, we explore three fundamental tail behavior patterns for univariate margins. Capitalizing on the probabilistic features of tail non-exchangeability structures, we introduce graphical techniques and statistical tests designed for analyzing data that may manifest non-exchangeability in the joint tail. The effectiveness of the proposed approaches is illustrated through a simulation study and a practical example.

Suggested Citation

  • Paramahansa Pramanik, 2024. "Dependence on Tail Copula," J, MDPI, vol. 7(2), pages 1-26, April.
    • Handle: RePEc:gam:jjopen:v:7:y:2024:i:2:p:8-152:d:1369259
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    References listed on IDEAS

    as
    1. Takaaki Koike & Shogo Kato & Marius Hofert, 2021. "Measuring non-exchangeable tail dependence using tail copulas," Papers 2101.12262, arXiv.org, revised Feb 2023.
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