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Assessing bivariate tail non-exchangeable dependence

Author

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  • Hua, Lei
  • Polansky, Alan
  • Pramanik, Paramahansa

Abstract

Non-exchangeable dependence structures exist in the real world. In particular, when dependence patterns in joint distributional tails are important, such as in the fields of engineering, environmetrics and econometrics, one may need to detect the existence, and assess the strength of non-exchangeable dependence patterns in the tails. In this paper, we propose a sensible metric to quantify the degree of tail non-exchangeability of bivariate copulas. Based on the metric, we propose a practical method of assessing tail non-exchangeable dependence with uniform scores of bivariate data. An empirical example is used to demonstrate the usefulness of the proposed method.

Suggested Citation

  • Hua, Lei & Polansky, Alan & Pramanik, Paramahansa, 2019. "Assessing bivariate tail non-exchangeable dependence," Statistics & Probability Letters, Elsevier, vol. 155(C), pages 1-1.
    • Handle: RePEc:eee:stapro:v:155:y:2019:i:c:14
    DOI: 10.1016/j.spl.2019.108556
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    References listed on IDEAS

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    9. Hua, Lei & Joe, Harry, 2014. "Strength of tail dependence based on conditional tail expectation," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 143-159.
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    Cited by:

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    4. Paramahansa Pramanik & Alan M. Polansky, 2023. "Scoring a Goal Optimally in a Soccer Game Under Liouville-Like Quantum Gravity Action," SN Operations Research Forum, Springer, vol. 4(3), pages 1-39, September.

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