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Measuring CoVaR: An Empirical Comparison

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  • Michele Leonardo Bianchi

    (Bank of Italy)

  • Alberto Maria Sorrentino

    (Bank of Italy)

Abstract

Recent literature has proposed a market-based measure to assess the contribution of a single bank to the systemic risk, i.e. the delta conditional value-at-risk ($$\Delta { CoVaR}$$ΔCoVaR). This measure could be useful to control the dynamics of systemic risk as perceived by the market. We estimate the $$\Delta { CoVaR}$$ΔCoVaR of Italian and main European banks over the time span from January 2007 to December 2018 by considering three possible methodologies: (1) the quantile regression; (2) a closed form formula; (3) a non-parametric method. The estimates based on closed form formula do not differ substantially from those of the other two methodologies, moreover they provide more robust results. Furthermore, we compare the ranking derived by the $$\Delta { CoVaR}$$ΔCoVaR with the global systemically important banks (GSIBs) buckets determining additional loss absorbency requirements. We show that there are differences in the ranking defined by the $$\Delta { CoVaR}$$ΔCoVaR and the GSIBs bucket allocation provided by the Financial Stability Board even if the $$\Delta { CoVaR}$$ΔCoVaR seems to be able to divide the good from the bad, from a systemic risk perspective.

Suggested Citation

  • Michele Leonardo Bianchi & Alberto Maria Sorrentino, 2020. "Measuring CoVaR: An Empirical Comparison," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 511-528, February.
    • Handle: RePEc:kap:compec:v:55:y:2020:i:2:d:10.1007_s10614-019-09901-2
    DOI: 10.1007/s10614-019-09901-2
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Mohammed Berkhouch & Fernanda Maria Müller & Ghizlane Lakhnati & Marcelo Brutti Righi, 2022. "Deviation-Based Model Risk Measures," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 527-547, February.
    3. Fuchs Sebastian & Trutschnig Wolfgang, 2020. "On quantile based co-risk measures and their estimation," Dependence Modeling, De Gruyter, vol. 8(1), pages 396-416, January.
    4. Pierre Nkou Mananga & Shiqiang Lin & Hairui Zhang, 2023. "A network approach to interbank contagion risk in South Africa," Working Papers 11052, South African Reserve Bank.
    5. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    6. Michele Leonardo Bianchi & Alberto Maria Sorrentino, 2022. "Exploring the Systemic Risk of Domestic Banks with ΔCoVaR and Elastic-Net," Journal of Financial Services Research, Springer;Western Finance Association, vol. 62(1), pages 127-141, October.
    7. Fuchs Sebastian & Trutschnig Wolfgang, 2020. "On quantile based co-risk measures and their estimation," Dependence Modeling, De Gruyter, vol. 8(1), pages 396-416, January.
    8. Bianchi, Michele Leonardo & De Luca, Giovanni & Rivieccio, Giorgia, 2023. "Non-Gaussian models for CoVaR estimation," International Journal of Forecasting, Elsevier, vol. 39(1), pages 391-404.

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