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Do banks overstate their Value-at-Risk?

  • Pérignon, Christophe
  • Deng, Zi Yin
  • Wang, Zhi Jun
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    This paper is the first empirical study of banks' risk management systems based on non-anonymous daily Value-at-Risk (VaR) and profit-and-loss data. Using actual data from the six largest Canadian commercial banks, we uncover evidence that banks exhibit a systematic excess of conservatism in their VaR estimates. The data used in this paper have been extracted from the banks' annual reports using an innovative Matlab-based data extraction method. Out of the 7354 trading days analyzed in this study, there are only two exceptions, i.e. days when the actual loss exceeds the disclosed VaR, whereas the expected number of exceptions with a 99% VaR is 74. For each sample bank, we extract from historical VaRs a risk-overstatement coefficient, ranging between 19 and 79%. We attribute VaR overstatement to several factors, including extreme cautiousness and underestimation of diversification effects when aggregating VaRs across business lines and/or risk categories. We also discuss the economic and social cost of reporting inflated VaRs.

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    Article provided by Elsevier in its journal Journal of Banking & Finance.

    Volume (Year): 32 (2008)
    Issue (Month): 5 (May)
    Pages: 783-794

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    Handle: RePEc:eee:jbfina:v:32:y:2008:i:5:p:783-794
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    1. Suleyman Basak & Alex Shapiro, . "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," Rodney L. White Center for Financial Research Working Papers 06-99, Wharton School Rodney L. White Center for Financial Research.
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    14. Lucas, Andre, 2001. "Evaluating the Basle Guidelines for Backtesting Banks' Internal Risk Management Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 33(3), pages 826-46, August.
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    17. 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.).
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