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Methods for evaluating value-at-risk estimates

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Author Info
Jose Lopez

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Abstract

Beginning in 1998, U.S. commercial banks with significant trading activities must hold capital against their defined market risk exposure. Under the current regulatory guidelines, this capital charge is a function of banks' own value-at-risk (VaR) estimates. Two hypothesis-testing methods for evaluating VaR estimates have been proposed; namely, the binomial and the interval forecast methods. As shown in a simulation exercise, the tests generally have low power and thus are prone to misclassifying inaccurate VaR estimates as "acceptably accurate". An alternative evaluation method, based on loss functions that capture specific regulatory concerns, is proposed. Simulation results indicate that this method is capable of distinguishing between VaR estimates generated by accurate and alternative VaR models. The additional information provided by this method, as well as its flexibility with respect to the specification of the loss function, make a reasonable case for its use in the regulatory evaluation of VaR estimates.

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Paper provided by Federal Reserve Bank of New York in its series Research Paper with number 9802.

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Date of creation: 1998
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Handle: RePEc:fip:fednrp:9802

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Keywords: Bank capital Risk Bank investments

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
  2. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," Center for Financial Institutions Working Papers 97-37, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
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  3. Phillip Kearns & Adrian Pagan, 1997. "Estimating The Density Tail Index For Financial Time Series," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 171-175, May. [Downloadable!] (restricted)
  4. Matthew Pritsker, 1997. "Evaluating Value at Risk Methodologies: Accuracy versus Computational Time," Journal of Financial Services Research, Springer, vol. 12(2), pages 201-242, October. [Downloadable!] (restricted)
  5. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  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. [Downloadable!]
  8. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Proceedings, Federal Reserve Bank of Chicago, issue May, pages 334-362.
  9. C. W.J. Granger & M. Hashem Pesaran, 1996. "A Decision Theoretic Approach to Forecast Evaluation," University of California at San Diego, Economics Working Paper Series 96-23, Department of Economics, UC San Diego.
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  10. Jose Lopez, 1998. "Methods for evaluating value-at-risk estimates," Research Paper 9802, Federal Reserve Bank of New York. [Downloadable!]
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  11. Matthew Pritsker, 1996. "Evaluating Value-at-Risk Methodologies: Accuracy versus Computational Time," Center for Financial Institutions Working Papers 96-48, Wharton School Center for Financial Institutions, University of Pennsylvania. [Downloadable!]
  12. Paul H. Kupiec & James M. O'Brien, 1995. "A pre-commitment approach to capital requirements for market risk," Proceedings, Federal Reserve Bank of Chicago, issue May, pages 552-562.
  13. Jose A. Lopez, 1997. "Regulatory evaluation of value-at-risk models," Staff Reports 33, Federal Reserve Bank of New York. [Downloadable!]
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  14. Paul H. Kupiec & James M. O'Brien, 1995. "A pre-commitment approach to capital requirements for market risk," Finance and Economics Discussion Series 95-36, Board of Governors of the Federal Reserve System (U.S.).
  15. 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.).
  16. 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 841-62, November.
  17. Darryll Hendricks & Beverly Hirtle, 1997. "Bank capital requirements for market risk: the internal models approach," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 1-12. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Trino-Manuel Ñíguez, 2003. "Volatility And Var Forecasting For The Ibex-35 Stock-Return Index Using Figarch-Type Processes And Different Evaluation Criteria," Working Papers. Serie AD 2003-33, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie). [Downloadable!]
  2. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics. [Downloadable!]
  3. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
  4. Jose A. Lopez, 1998. "Methods for evaluating value-at-risk estimates," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 119-124. [Downloadable!]
    Other versions:
  5. 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. [Downloadable!]
  6. Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group. [Downloadable!]
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  7. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti". [Downloadable!]
  8. Bahram Pesaran & M. Hashem Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH. [Downloadable!]
  9. Jose A. Lopez & Christian A. Walter, 2000. "Evaluating covariance matrix forecasts in a value-at-risk framework," Working Papers in Applied Economic Theory 2000-21, Federal Reserve Bank of San Francisco. [Downloadable!]
  10. Luiz Renato Regis de Oliveira Lima & Breno de Andrade Pinheiro Neri, 2006. "Comparing Value-at-Risk Methodologies," Economics Working Papers (Ensaios Economicos da EPGE) 629, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
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  11. Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor and Francis Journals, vol. 14(18), pages 1333-1342, December. [Downloadable!] (restricted)
  12. Chien-Liang Chiu & Ming-Chih Lee & Jui-Cheng Hung, 2005. "Estimation of Value-at-Risk under jump dynamics and asymmetric information," Applied Financial Economics, Taylor and Francis Journals, vol. 15(15), pages 1095-1106, October. [Downloadable!] (restricted)
  13. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute. [Downloadable!]
  14. Jose A. Lopez & Marc R. Saidenberg, 1999. "Evaluating credit risk models," Working Papers in Applied Economic Theory 99-06, Federal Reserve Bank of San Francisco. [Downloadable!]
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