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Market risk management of banks: implications from the accuracy of Value-at-Risk forecasts


  • Wai Yan Cheng

    (Department of Economics and Finance, City University of Hong Kong, Hong Kong)

  • Michael Chak Sham Wong

    (Department of Economics and Finance, City University of Hong Kong, Hong Kong)

  • Clement Yuk Pang Wong

    (Department of Economics and Finance, City University of Hong Kong, Hong Kong)


This paper adopts the backtesting criteria of the Basle Committee to compare the performance of a number of simple Value-at-Risk (VaR) models. These criteria provide a new standard on forecasting accuracy. Currently central banks in major money centres, under the auspices of the Basle Committee of the Bank of International settlement, adopt the VaR system to evaluate the market risk of their supervised banks. Banks are required to report VaRs to bank regulators with their internal models. These models must comply with Basle's backtesting criteria. If a bank fails the VaR backtesting, higher capital requirements will be imposed. VaR is a function of volatility forecasts. Past studies mostly conclude that ARCH and GARCH models provide better volatility forecasts. However, this paper finds that ARCH- and GARCH-based VaR models consistently fail to meet Basle's backtesting criteria. These findings suggest that the use of ARCH- and GARCH-based models to forecast their VaRs is not a reliable way to manage a bank's market risk. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Wai Yan Cheng & Michael Chak Sham Wong & Clement Yuk Pang Wong, 2003. "Market risk management of banks: implications from the accuracy of Value-at-Risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 23-33.
  • Handle: RePEc:jof:jforec:v:22:y:2003:i:1:p:23-33 DOI: 10.1002/for.842

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    References listed on IDEAS

    1. 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.).
    2. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
    3. West, Kenneth D. & Cho, Dongchul, 1995. "The predictive ability of several models of exchange rate volatility," Journal of Econometrics, Elsevier, vol. 69(2), pages 367-391, October.
    4. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
    5. Baillie, Richard T. & Bollerslev, Tim, 1992. "Prediction in dynamic models with time-dependent conditional variances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 91-113.
    6. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    7. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Economic Policy Review, Federal Reserve Bank of New York, issue Apr, pages 39-69.
    8. Patricia Jackson & David Maude & William Perraudin, 1998. "Bank Capital and Value at Risk," Bank of England working papers 79, Bank of England.
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    Cited by:

    1. Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016. "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, vol. 43(1 Year 20), pages 29-52, June.

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