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Measuring and regulating extreme risk

Author

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  • Ulf Nielsson

Abstract

Purpose - The purpose of this paper is to discuss two important extensions to the well‐known value‐at‐risk (VaR) methodology, namely extreme value theory (EVT) and expected shortfall (ES). Both of these extensions address the weaknesses of VaR, in particular the methodology's tendency to systematically underestimate risk of extreme market events. Design/methodology/approach - The theory of VaR and the two extensions are reviewed and the methodology is evaluated in light of the Basel II regulatory framework that calls for the use of VaR by financial institutions. Findings - The paper clarifies the use of VaR and its extensions to make practitioners more aware of the pitfalls and how to address them. It is recommended that the two extended measures of extreme event risk (i.e. EVT and ES) be included into every risk manager's information pool. Originality/value - A compact review of these approaches and their regulatory connection has not previously been compiled. This review is of particular value to risk managers and policy markers given the turbulent market conditions of the past year.

Suggested Citation

  • Ulf Nielsson, 2009. "Measuring and regulating extreme risk," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 17(2), pages 156-171, May.
    • Handle: RePEc:eme:jfrcpp:v:17:y:2009:i:2:p:156-171
    DOI: 10.1108/13581980910952595
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    Citations

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    Cited by:

    1. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    2. Bogdan ZUGRAVU & Dumitru Cristian OANEA & Victoria Gabriela ANGHELACHE, 2013. "Analysis Based on the Risk Metrics Model," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(2), pages 145-154, May.
    3. Salehi , Mahdi & Zamani , Mohammad, 2014. "Market Risk Recognition by Different Models in Listed Banks of Tehran Stock Exchange and OTC," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 9(1), pages 147-176, October.
    4. Dumitru Cristian OANEA & Victoria Gabriela ANGHELACHE & Bogdan ZUGRAVU, 2013. "Econometric Model for Risk Forecasting," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(2), pages 123-127, May.
    5. Zdeněk Konečný & Marek Zinecker, 2016. "Optimizing Risk Structure in Connection with the Corporate Life Cycle and Sector Cyclicity," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(3), pages 949-959.
    6. Zdeněk Konečný & Marek Zinecker, 2015. "Measuring Risk Structure Using the Capital Asset Pricing Model," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(1), pages 227-233.

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