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CoVaR of families of copulas

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  • Bernardi, M.
  • Durante, F.
  • Jaworski, P.

Abstract

We revisit the notion of Conditional Value-at-Risk (shortly, CoVaR) by weakening the usual assumptions on the joint distribution function of the involved random variables. The new approach exploits the copula methodology and uses the concept of Dini derivatives. A directory of CoVaR values for different families of copulas is provided.

Suggested Citation

  • Bernardi, M. & Durante, F. & Jaworski, P., 2017. "CoVaR of families of copulas," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 8-17.
    • Handle: RePEc:eee:stapro:v:120:y:2017:i:c:p:8-17
    DOI: 10.1016/j.spl.2016.09.005
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    References listed on IDEAS

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    5. Mauro Bernardi & Lea Petrella, 2015. "Interconnected Risk Contributions: A Heavy-Tail Approach to Analyze U.S. Financial Sectors," JRFM, MDPI, vol. 8(2), pages 1-29, April.
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    Cited by:

    1. Li, Songsong & Zhang, Weiqian & Zhang, Wei, 2023. "Dynamic time-frequency connectedness and risk spillover between geopolitical risks and natural resources," Resources Policy, Elsevier, vol. 82(C).
    2. Takaaki Koike & Marius Hofert, 2019. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Papers 1909.11794, arXiv.org, revised May 2020.
    3. Ortega-Jiménez, P. & Sordo, M.A. & Suárez-Llorens, A., 2021. "Stochastic orders and multivariate measures of risk contagion," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 199-207.
    4. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    5. Naeem, Muhammad Abubakr & Bouri, Elie & Costa, Mabel D. & Naifar, Nader & Shahzad, Syed Jawad Hussain, 2021. "Energy markets and green bonds: A tail dependence analysis with time-varying optimal copulas and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    6. Ortega-Jiménez, Patricia & Pellerey, Franco & Sordo, Miguel A. & Suárez-Llorens, Alfonso, 2024. "Probability equivalent level for CoVaR and VaR," Insurance: Mathematics and Economics, Elsevier, vol. 115(C), pages 22-35.
    7. Xun, Li & Jiang, Renqiao & Guo, Jianhua, 2021. "The conditional Haezendonck–Goovaerts risk measure," Statistics & Probability Letters, Elsevier, vol. 169(C).
    8. Sordo, M.A. & Bello, A.J. & Suárez-Llorens, A., 2018. "Stochastic orders and co-risk measures under positive dependence," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 105-113.
    9. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    10. Aleksy Leeuwenkamp & Wentao Hu, 2023. "New general dependence measures: construction, estimation and application to high-frequency stock returns," Papers 2309.00025, arXiv.org.
    11. Piotr Jaworski & Anna Zalewska, 2024. "Portfolio Selection Based on Modified CoVaR in Gaussian Framework," Mathematics, MDPI, vol. 12(23), pages 1-23, November.
    12. Takaaki Koike & Marius Hofert, 2020. "Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations," Risks, MDPI, vol. 8(1), pages 1-33, January.
    13. Mauro Bernardi & Roy Cerqueti & Arsen Palestini, 2020. "The Skew Normal multivariate risk measurement framework," Computational Management Science, Springer, vol. 17(1), pages 105-119, January.

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