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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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    1. Fabrizio Durante & Erich Klement & Carlo Sempi & Manuel Úbeda-Flores, 2010. "Measures of non-exchangeability for bivariate random vectors," Statistical Papers, Springer, vol. 51(3), pages 687-699, September.
    2. Christian Genest & Kilani Ghoudi & Louis-Paul Rivest, 1998. "“Understanding Relationships Using Copulas,” by Edward Frees and Emiliano Valdez, January 1998," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(3), pages 143-149.
    3. Roger Nelsen, 2007. "Extremes of nonexchangeability," Statistical Papers, Springer, vol. 48(4), pages 695-695, October.
    4. Hua, Lei & Joe, Harry, 2017. "Multivariate dependence modeling based on comonotonic factors," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 317-333.
    5. Furman, Edward & Su, Jianxi & Zitikis, RiÄ ardas, 2015. "Paths And Indices Of Maximal Tail Dependence," ASTIN Bulletin, Cambridge University Press, vol. 45(3), pages 661-678, September.
    6. Hua, Lei & Joe, Harry, 2011. "Tail order and intermediate tail dependence of multivariate copulas," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1454-1471, November.
    7. Harder, Michael & Stadtmüller, Ulrich, 2014. "Maximal non-exchangeability in dimension d," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 31-41.
    8. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    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.
    10. Christian Genest & Johanna Nešlehová & Jean-François Quessy, 2012. "Tests of symmetry for bivariate copulas," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(4), pages 811-834, August.
    11. Edward Frees & Emiliano Valdez, 1998. "Understanding Relationships Using Copulas," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 1-25.
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    Cited by:

    1. Masud Alam, 2021. "Heterogeneous Responses to the U.S. Narrative Tax Changes: Evidence from the U.S. States," Papers 2107.13678, arXiv.org.
    2. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    3. 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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