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On the Validity of Value-at-Risk: Comparative Analyses with Expected Shortfall


  • Yamai, Yasuhiro

    (Institute for Monetary & Econ Studies, Bank of Japan)

  • Yoshiba, Toshinao

    (Institute for Monetary & Econ Studies, Bank of Japan)


Value-at-risk (VaR) has become a standard measure used in financial risk management due to its conceptual simplicity, computational facility, and ready applicability. However, many authors claim that VaR has several conceptual problems. Artzner et al. (1997, 1999), for example, have cited the following shortcomings of VaR. (1) VaR measures only percentiles of profit-loss distributions, and thus disregards any loss beyond the VaR level ("tail risk"), and (2) VaR is not coherent since it is not sub-additive. To alleviate the problems inherent in VaR, the use of expected shortfall is proposed. In this paper, we provide an overview of studies comparing VaR and expected shortfall to draw practical implications for financial risk management. In particular, we illustrate how tail risk can bring serious practical problems in some cases.

Suggested Citation

  • 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.
  • Handle: RePEc:ime:imemes:v:20:y:2002:i:1:p:57-85

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    References listed on IDEAS

    1. Rudebusch, Glenn D. & Svensson, Lars E. O., 2002. "Eurosystem monetary targeting: Lessons from U.S. data," European Economic Review, Elsevier, vol. 46(3), pages 417-442, March.
    2. Higo, Masahiro & Nakada, Sachiko-Kuroda, 1999. "What Determines the Relation between the Output Gap and Inflation ? An International Comparison of Inflation Expectations and Staggered Wage Adjustment," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 17(3), pages 129-155, December.
    3. Mori, Naruki & Shiratsuka, Shigenori & Taguchi, Hiroo, 2001. "Policy Responses to the Post-bubble Adjustments in Japan: A Tentative Review," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 19(S1), pages 53-102, February.
    4. Okina, Kunio & Shirakawa, Masaaki & Shiratsuka, Shigenori, 2001. "The Asset Price Bubble and Monetary Policy: Japan's Experience in the Late 1980s and the Lessons: Background Paper," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 19(S1), pages 395-450, February.
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    Cited by:

    1. Mario Domingues de Paula Simões & Marcelo Cabus Klotzle & Antonio Carlos Figueiredo Pinto & Leonardo Lima Gomes, 2016. "Electricity prices forecast analysis using the extreme value theory," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 1-22.
    2. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
    3. Sebastian Bayer & Timo Dimitriadis, 2018. "Regression Based Expected Shortfall Backtesting," Papers 1801.04112,
    4. Kerkhof, Jeroen & Melenberg, Bertrand, 2004. "Backtesting for risk-based regulatory capital," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1845-1865, August.
    5. Kim, Minjo & Lee, Sangyeol, 2016. "Nonlinear expectile regression with application to Value-at-Risk and expected shortfall estimation," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 1-19.
    6. Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2008. "Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization," Management Science, INFORMS, vol. 54(3), pages 573-585, March.
    7. Fermanian, Jean-David & Scaillet, Olivier, 2005. "Sensitivity analysis of VaR and Expected Shortfall for portfolios under netting agreements," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 927-958, April.
    8. Osmundsen, Kjartan Kloster, 2017. "Using Expected Shortfall for Credit Risk Regulation," UiS Working Papers in Economics and Finance 2017/4, University of Stavanger.

    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill


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