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On Conditional Value at Risk (CoVaR) for tail-dependent copulas

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  • Jaworski Piotr

    (Institute of Mathematics, University of Warsaw, Poland)

Abstract

The paper deals with Conditional Value at Risk (CoVaR) for copulas with nontrivial tail dependence. We show that both in the standard and the modified settings, the tail dependence function determines the limiting properties of CoVaR as the conditioning event becomes more extreme. The results are illustrated with examples using the extreme value, conic and truncation invariant families of bivariate tail-dependent copulas.

Suggested Citation

  • Jaworski Piotr, 2017. "On Conditional Value at Risk (CoVaR) for tail-dependent copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 1-19, January.
    • Handle: RePEc:vrs:demode:v:5:y:2017:i:1:p:1-19:n:1
    DOI: 10.1515/demo-2017-0001
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    References listed on IDEAS

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    1. Li, Haijun & Wu, Peiling, 2013. "Extremal dependence of copulas: A tail density approach," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 99-111.
    2. 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.
    3. Charpentier, Arthur & Segers, Johan, 2009. "Tails of multivariate Archimedean copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1521-1537, August.
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    5. Juri, Alessandro & Wuthrich, Mario V., 2002. "Copula convergence theorems for tail events," Insurance: Mathematics and Economics, Elsevier, vol. 30(3), pages 405-420, June.
    6. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    7. Paul Embrechts, 2009. "Copulas: A Personal View," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 639-650, September.
    8. Durante, Fabrizio & Jaworski, Piotr & Mesiar, Radko, 2011. "Invariant dependence structures and Archimedean copulas," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1995-2003.
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    Cited by:

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    2. Takaaki Koike & Marius Hofert, 2020. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Risks, MDPI, vol. 8(1), pages 1-33, January.

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