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TERES: Tail Event Risk Expectile Shortfall

Author

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  • Andrija Mihoci
  • Wolfgang Karl Härdle
  • Cathy Yi-Hsuan Chen

Abstract

We propose a generalized risk measure for expectile-based expected shortfall estimation. The generalization is designed with a mixture of Gaussian and Laplace densities. Our plug-in estimator is derived from an analytic relationship between expectiles and expected shortfall. We investigate the sensitivity and robustness of the expected shortfall to the underlying mixture parameter specification and the risk level. Empirical results from the US, German and UK stock markets and for selected NASDAQ blue chip companies indicate that expected shortfall can be successfully estimated using the proposed method on a monthly, weekly, daily and intra-day basis using a 1-year or 1-day time horizon across different risk levels.

Suggested Citation

  • Andrija Mihoci & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2021. "TERES: Tail Event Risk Expectile Shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 21(3), pages 449-460, March.
    • Handle: RePEc:taf:quantf:v:21:y:2021:i:3:p:449-460
    DOI: 10.1080/14697688.2020.1786151
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    Cited by:

    1. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).

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