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The level and quality of Value-at-Risk disclosure by commercial banks

Author

Listed:
  • Christophe Perignon

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Daniel R. Smith

    (Faculty of Business Administration - SFU.ca - Simon Fraser University)

Abstract

In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996-2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.

Suggested Citation

  • Christophe Perignon & Daniel R. Smith, 2010. "The level and quality of Value-at-Risk disclosure by commercial banks," Post-Print hal-00528391, HAL.
  • Handle: RePEc:hal:journl:hal-00528391
    DOI: 10.1016/j.jbankfin.2009.08.009
    Note: View the original document on HAL open archive server: https://hal-hec.archives-ouvertes.fr/hal-00528391
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    1. James W. Taylor, 2005. "Generating Volatility Forecasts from Value at Risk Estimates," Management Science, INFORMS, vol. 51(5), pages 712-725, May.
    2. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value-at-Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, June.
    3. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-548, National Bureau of Economic Research, Inc.
    4. Bali, Turan G. & Gokcan, Suleyman & Liang, Bing, 2007. "Value at risk and the cross-section of hedge fund returns," Journal of Banking & Finance, Elsevier, vol. 31(4), pages 1135-1166, April.
    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. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    7. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Danielsson, Jon & Jorgensen, Bjorn N. & de Vries, Casper G., 2002. "Incentives for effective risk management," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1407-1425, July.
    10. Pérignon, Christophe & Deng, Zi Yin & Wang, Zhi Jun, 2008. "Do banks overstate their Value-at-Risk?," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 783-794, May.
    11. Beverly Hirtle, 2016. "Public disclosure and risk-adjusted performance at bank holding companies," Economic Policy Review, Federal Reserve Bank of New York, issue Aug, pages 151-173.
    12. Philippe Jorion, 2007. "Bank Trading Risk and Systemic Risk," NBER Chapters, in: The Risks of Financial Institutions, pages 29-58, National Bureau of Economic Research, Inc.
    13. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
    14. Darryll Hendricks & Beverly Hirtle, 1997. "Bank capital requirements for market risk: the internal models approach," Economic Policy Review, Federal Reserve Bank of New York, vol. 3(Dec), pages 1-12.
    15. James M. O'Brien & Jeremy Berkowitz, 2007. "Estimating Bank Trading Risk. A Factor Model Approach," NBER Chapters, in: The Risks of Financial Institutions, pages 59-102, National Bureau of Economic Research, Inc.
    16. Brenner, Robin J. & Harjes, Richard H. & Kroner, Kenneth F., 1996. "Another Look at Models of the Short-Term Interest Rate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(1), pages 85-107, March.
    17. Barth, James R.*Caprio,Gerard*Levine, Ross, 2001. "The regulation and supervision of banks around the world - a new database," Policy Research Working Paper Series 2588, The World Bank.
    18. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    19. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    20. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    21. R. Glen Donaldson & Mark J. Kamstra, 2005. "Volatility Forecasts, Trading Volume, And The Arch Versus Option‐Implied Volatility Trade‐Off," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(4), pages 519-538, December.
    22. Cuoco, Domenico & Liu, Hong, 2006. "An analysis of VaR-based capital requirements," Journal of Financial Intermediation, Elsevier, vol. 15(3), pages 362-394, July.
    23. Beverly Hirtle, 2003. "What market risk capital reporting tells us about bank risk," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 37-54.
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