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Using Expected Shortfall for Credit Risk Regulation

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  • Osmundsen, Kjartan Kloster

    (UiS)

Abstract

The Basel Committee’s minimum capital requirement function for banks’ credit risk is based on value at risk. This paper performs a statistical and economic analysis of the consequences of instead basing it on expected shortfall, a switch that has already been set in motion for market risk. The empirical analysis is carried out by means of both theoretical simulations and real data from a Norwegian savings bank group’s corporate portfolio. Expected shortfall has some well known conceptual advantages compared to value at risk, primarily a better ability to capture tail risk. It is also sub-additive in gen- eral, thus always reflecting the positive effect of diversification. These two aspects are examined in detail, in addition to comparing parameter sensitivity, estimation stabil- ity and backtesting methods for the two risk measures. All comparisons are conducted within the Basel Committee’s minimum capital requirement framework. The findings support a switch from value at risk to expected shortfall for credit risk modelling.

Suggested Citation

  • Osmundsen, Kjartan Kloster, 2017. "Using Expected Shortfall for Credit Risk Regulation," UiS Working Papers in Economics and Finance 2017/4, University of Stavanger.
  • Handle: RePEc:hhs:stavef:2017_004
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    File URL: http://www1.uis.no/ansatt/odegaard/uis_wps_econ_fin/uis_wps_2017_04_osmundsen.pdf
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    References listed on IDEAS

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    1. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    2. Carlo Acerbi & Dirk Tasche, 2002. "Expected Shortfall: A Natural Coherent Alternative to Value at Risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(2), pages 379-388, July.
    3. Susanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What is the best risk measure in practice? A comparison of standard measures," Papers 1312.1645, arXiv.org, revised Apr 2015.
    4. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    5. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    6. Yamai, Yasuhiro & Yoshiba, Toshinao, 2002. "Comparative Analyses of Expected Shortfall and Value-at-Risk: Their Estimation Error, Decomposition, and Optimization," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 20(1), pages 87-121, January.
    7. Koch-Medina, Pablo & Munari, Cosimo, 2016. "Unexpected shortfalls of Expected Shortfall: Extreme default profiles and regulatory arbitrage," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 141-151.
    8. Martin Hibbeln, 2010. "Risk Management in Credit Portfolios," Contributions to Economics, Springer, number 978-3-7908-2607-4, May.
    9. 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.
    10. Daníelsson, Jón & Jorgensen, Bjørn N. & Samorodnitsky, Gennady & Sarma, Mandira & de Vries, Casper G., 2013. "Fat tails, VaR and subadditivity," Journal of Econometrics, Elsevier, vol. 172(2), pages 283-291.
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    More about this item

    Keywords

    Expected shortfall; credit risk; bank regulation; Basel III; tail risk;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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