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Modified Expected Shortfall: a Coherent Risk Measure for Elliptical Family of Distributions

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  • Deepak K. Jadhav

    (Savitribai Phule Pune University)

  • Ramanathan Thekke Variyam

    (Savitribai Phule Pune University)

Abstract

The ‘Modified Expected Shortfall’ is a risk measure proposed by Jadhav et al. (J. Risk 16, 69–83, 2013) is not a coherent risk measure in general. In this paper, we prove that ‘Modified Expected Shortfall’ is a coherent risk measure under univariate and multivariate elliptical families of distributions. The Modified Expected Shortfall performs better than the Expected Shortfall and is found to be lower in magnitude. Backtesting results support the superiority of Modified Expected Shortfall when compared with the Expected Shortfall.

Suggested Citation

  • Deepak K. Jadhav & Ramanathan Thekke Variyam, 2023. "Modified Expected Shortfall: a Coherent Risk Measure for Elliptical Family of Distributions," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 234-256, May.
  • Handle: RePEc:spr:sankhb:v:85:y:2023:i:1:d:10.1007_s13571-022-00294-1
    DOI: 10.1007/s13571-022-00294-1
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    References listed on IDEAS

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    1. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    2. Susanne Emmer & Marie Kratz & Dirk Tasche, . "What is the best risk measure in practice? A comparison of standard measures," Journal of Risk, Journal of Risk.
    3. Yamai, Yasuhiro & Yoshiba, Toshinao, 2002. "On the Validity of Value-at-Risk: Comparative Analyses with Expected Shortfall," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 20(1), pages 57-85, January.
    4. Zinoviy Landsman & Emiliano Valdez, 2003. "Tail Conditional Expectations for Elliptical Distributions," North American Actuarial Journal, Taylor & Francis Journals, vol. 7(4), pages 55-71.
    5. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    6. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    7. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2015. "Shortfall Deviation Risk: An alternative to risk measurement," Papers 1501.02007, arXiv.org, revised May 2016.
    8. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    9. Cambanis, Stamatis & Huang, Steel & Simons, Gordon, 1981. "On the theory of elliptically contoured distributions," Journal of Multivariate Analysis, Elsevier, vol. 11(3), pages 368-385, September.
    10. Inui, Koji & Kijima, Masaaki, 2005. "On the significance of expected shortfall as a coherent risk measure," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 853-864, April.
    11. Carlo Acerbi & Claudio Nordio & Carlo Sirtori, 2001. "Expected Shortfall as a Tool for Financial Risk Management," Papers cond-mat/0102304, arXiv.org.
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