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Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures


  • Denisa Banulescu

    (University of Orleans; Maastricht School of Business and Economics)

  • Christophe Hurlin

    (University of Orleans)

  • Jeremy Leymarie

    (University of Orleans)

  • O. Scaillet

    (University of Geneva GSEM and GFRI; Swiss Finance Institute; University of Geneva - Research Center for Statistics)


This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Our procedure is based on simple tests similar to those generally used to backtest the standard market risk measures such as value-at-risk or expected shortfall. We introduce a concept of violation associated with the marginal expected shortfall (MES), and we define unconditional coverage and independence tests for these violations. We can generalize these tests to any MES-based systemic risk measures such as SES, SRISK, or ∆CoVaR. We study their asymptotic properties in the presence of estimation risk and investigate their finite sample performance via Monte Carlo simulations. An empirical application is then carried out to check the validity of the MES, SRISK, and ∆CoVaR forecasts issued from a GARCH-DCC model for a panel of U.S. financial institutions. Our results show that this model is able to produce valid forecasts for the MES and SRISK when considering a medium-term horizon. Finally, we propose an original early warning system indicator for future systemic crises deduced from these backtests. We then define an adjusted systemic risk measure that takes into account the potential misspecification of the risk model.

Suggested Citation

  • Denisa Banulescu & Christophe Hurlin & Jeremy Leymarie & O. Scaillet, 2019. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Swiss Finance Institute Research Paper Series 19-48, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp1948

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    Cited by:

    1. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    2. Qin, Xiao & Zhou, Chen, 2021. "Systemic risk allocation using the asymptotic marginal expected shortfall," Journal of Banking & Finance, Elsevier, vol. 126(C).

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