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A simulation-based method for estimating systemic risk measures

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  • Ye, Wuyi
  • Zhou, Yi
  • Chen, Pengzhan
  • Wu, Bin

Abstract

This paper focuses on simulation-based approaches for estimating systemic risk measures. In particular, we provide the asymptotic forms of the relative errors for widely used systemic risk measures including conditional value-at-risk (CoVaR), coexpected shortfall (CoES) and marginal expected shortfall (MES). Based on asymptotic expansions, a general framework is provided for the simulation of systemic risk measures. The numerical results show that the proposed simulation framework works well, and it is more user-friendly, easier to expand and less time-consuming than simulation approaches using the resampling method and importance sampling.

Suggested Citation

  • Ye, Wuyi & Zhou, Yi & Chen, Pengzhan & Wu, Bin, 2024. "A simulation-based method for estimating systemic risk measures," European Journal of Operational Research, Elsevier, vol. 313(1), pages 312-324.
    • Handle: RePEc:eee:ejores:v:313:y:2024:i:1:p:312-324
    DOI: 10.1016/j.ejor.2023.08.032
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