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Regulatory evaluation of value-at-risk models

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  • Jose A. Lopez

Abstract

Beginning in 1998, commercial banks may determine their regulatory capital requirements for market risk exposure using value-at-risk (VaR) models; i.e., time-series models of the distributions of portfolio returns. Currently, regulators have available three statistical methods for evaluating the accuracy of VaR models: the binomial method, the interval forecast method, and the distribution forecast method. These methods test whether the VaR forecasts in question exhibit properties characteristics of accurate VaR forecasts. However, the statistical tests can have low power against alternative models. A new evaluation method, based on proper scoring rules for probability forecasts, is proposed. Simulation results indicate that this method is clearly capable of differentiating among accurate and alternative VaR models.

Suggested Citation

  • Jose A. Lopez, 1997. "Regulatory evaluation of value-at-risk models," Research Paper 9710, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednrp:9710
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    1. Paul H. Kupiec & James M. O'Brien, 1995. "A pre-commitment approach to capital requirements for market risk," Proceedings 475, Federal Reserve Bank of Chicago.
    2. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, "undated". "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
    3. 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.).
    4. Granger, C. W. J. & White, Halbert & Kamstra, Mark, 1989. "Interval forecasting : An analysis based upon ARCH-quantile estimators," Journal of Econometrics, Elsevier, vol. 40(1), pages 87-96, January.
    5. Dimson, Elroy & Marsh, Paul, 1995. "Capital Requirements for Securities Firms," Journal of Finance, American Finance Association, vol. 50(3), pages 821-851, July.
    6. 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.
    7. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    8. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    9. 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.
    10. Arturo Estrella, 1995. "A prolegomenon to future capital requirements," Economic Policy Review, Federal Reserve Bank of New York, issue Jul, pages 1-12.
    11. Darryll Hendricks, 1996. "Evaluation of value-at-risk models using historical data," Economic Policy Review, Federal Reserve Bank of New York, vol. 2(Apr), pages 39-69.
    12. J. S. Butler & Barry Schachter, 1996. "Improving Value-At-Risk Estimates By Combining Kernel Estimation With Historical Simulation," Finance 9605001, University Library of Munich, Germany.
    13. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    14. Granger, C.W.J. & Pesaran, H., 1996. "A Decision_Theoretic Approach to Forecast Evaluation," Cambridge Working Papers in Economics 9618, Faculty of Economics, University of Cambridge.
    15. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    16. Paul H. Kupiec & James M. O'Brien, 1995. "The use of bank trading risk models for regulatory capital purposes," Finance and Economics Discussion Series 95-11, Board of Governors of the Federal Reserve System (U.S.).
    17. J. S. Butler & Barry Schachter, 1996. "Improving value-at-risk estimates by combining kernel estimation," Proceedings 513, Federal Reserve Bank of Chicago.
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    Cited by:

    1. 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.).
    2. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    3. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    4. Mark R. Manfredo. & Raymond M. Leuthold, 1999. "Market Risk Measurement and the Cattle Feeding Margin: An Application of Value-at-Risk," Finance 9908002, University Library of Munich, Germany.
    5. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    6. José Santiago Fajardo Barbachan & Aquiles Rocha de Farias & José Renato Haas Ornelas, 2008. "A Goodness-of-Fit Test with Focus on Conditional Value at Risk," Brazilian Review of Finance, Brazilian Society of Finance, vol. 6(2), pages 139-155.
    7. Aymen BEN REJEB & Ousama BEN SALHA & Jaleleddine BEN REJEB, 2012. "Value-at-Risk Analysis for the Tunisian Currency Market: A Comparative Study," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 110-125.
    8. Sean D. Campbell, 2005. "A review of backtesting and backtesting procedures," Finance and Economics Discussion Series 2005-21, Board of Governors of the Federal Reserve System (U.S.).
    9. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
    10. Michael Clements, 2006. "Evaluating the survey of professional forecasters probability distributions of expected inflation based on derived event probability forecasts," Empirical Economics, Springer, vol. 31(1), pages 49-64, March.
    11. Stephanos Papadamou & George Stephanides, 2004. "Evaluating the style-based risk model for equity mutual funds investing in Europe," Applied Financial Economics, Taylor & Francis Journals, vol. 14(10), pages 751-760.
    12. Glynn Tonsor & Ted Schroeder, 2011. "Multivariate forecasting of a commodity portfolio: application to cattle feeding margins and risk," Applied Economics, Taylor & Francis Journals, vol. 43(11), pages 1329-1339.
    13. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    14. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2009. "Asymmetric multivariate normal mixture GARCH," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2129-2154, April.
    15. Fiondella, Lance & Lin, Yi-Kuei & Pham, Hoang & Chang, Ping-Chen & Li, Chendong, 2017. "A confidence-based approach to reliability design considering correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 102-114.
    16. L. Kourouma & Denis Dupré & G. Sanfilippo & O. Taramasco, 2011. "Extreme Value at Risk and Expected Shortfall during Financial Crisis," Post-Print halshs-00658495, HAL.
    17. Michael P. Clements & Nick Taylor, 2003. "Evaluating interval forecasts of high-frequency financial data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 445-456.
    18. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    19. William E. Nganje & Mounir Siaplay & Simeon Kaitibie & Emmanuel T. Acquah, 2006. "Predicting food safety losses in turkey processing and the economic incentives of hazard analysis and critical control point (HACCP) intervention," Agribusiness, John Wiley & Sons, Ltd., vol. 22(4), pages 475-489.
    20. Xiongwei Ju & Neil D. Pearson, 1998. "Using Value-at-Risk to Control Risk Taking: How Wrong Can you Be?," Finance 9810002, University Library of Munich, Germany.
    21. Manfredo, Mark R. & Leuthold, Raymond M., 1999. "Measuring Market Risk Of The Cattle Feeding Margin: An Application Of Value-At-Risk Analysis," 1999 Annual meeting, August 8-11, Nashville, TN 21628, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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