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Invariant dependence structures and Archimedean copulas

Author

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  • Durante, Fabrizio
  • Jaworski, Piotr
  • Mesiar, Radko

Abstract

We consider a family of copulas that are invariant under univariate truncation. Such a family has some distinguishing properties: it is generated by means of a univariate function; it can capture non-exchangeable dependence structures; it can be easily simulated. Moreover, such a class presents strong probabilistic similarities with the class of Archimedean copulas from a theoretical and practical point of view.

Suggested Citation

  • Durante, Fabrizio & Jaworski, Piotr & Mesiar, Radko, 2011. "Invariant dependence structures and Archimedean copulas," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1995-2003.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:12:p:1995-2003
    DOI: 10.1016/j.spl.2011.08.018
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    References listed on IDEAS

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    1. Juri, Alessandro & Wuthrich, Mario V., 2002. "Copula convergence theorems for tail events," Insurance: Mathematics and Economics, Elsevier, vol. 30(3), pages 405-420, June.
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    3. Joe, Harry & Li, Haijun & Nikoloulopoulos, Aristidis K., 2010. "Tail dependence functions and vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 252-270, January.
    4. Christian Genest & Jean‐François Quessy & Bruno Rémillard, 2006. "Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 337-366, June.
    5. Claudia Klüppelberg & Gabriel Kuhn & Liang Peng, 2008. "Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 701-718, December.
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    Cited by:

    1. Bernardi, M. & Durante, F. & Jaworski, P., 2017. "CoVaR of families of copulas," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 8-17.
    2. Jaworski Piotr, 2017. "On Truncation Invariant Copulas and their Estimation," Dependence Modeling, De Gruyter, vol. 5(1), pages 133-144, January.
    3. Jaworski, Piotr, 2015. "Univariate conditioning of vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 89-103.
    4. Jaworski Piotr, 2023. "On copulas with a trapezoid support," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-23, January.
    5. Jaworski Piotr, 2017. "On Conditional Value at Risk (CoVaR) for tail-dependent copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 1-19, January.

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