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Regulatory evaluation of value-at-risk models

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  • Jose A. Lopez

Abstract

Beginning in 1998, U.S. commercial banks may determine their regulatory capital requirements for financial market risk exposure using value-at-risk (VaR) models i.e., models of the time-varying distributions of portfolio returns. Currently, regulators have available three hypothesis-testing methods for evaluating the accuracy of VaR models: the binomial method, the interval forecast method and the distribution forecast method. These methods use hypothesis tests to examine whether the VaR forecasts in question exhibit properties characteristic of accurate VaR forecasts. However, given the low power often exhibited by these tests, these methods may often misclassify forecasts from inaccurate models as accurate. A new evaluation method that uses loss functions based on probability forecasts, is proposed. Simulation results indicate that this method is capable of differentiating between forecasts from accurate and inaccurate, alternative VaR models.

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Bibliographic Info

Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 33.

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Date of creation: 1997
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Handle: RePEc:fip:fednsr:33

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Related research

Keywords: Risk ; Bank capital ; Econometric models ; Forecasting;

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References

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  1. 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.
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  10. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
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  13. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-35, April.
  14. 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.
  15. 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.
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Citations

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Cited by:
  1. 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.
  2. 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.
  3. 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.).
  4. 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.
  5. 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.
  6. 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.).
  7. L. Kourouma & D. Dupre & G. Sanfilippo & O. Taramasco, 2011. "Extreme Value at Risk and Expected Shortfall during Financial Crisis," Post-Print halshs-00658495, HAL.
  8. Xiongwei Ju & Neil D. Pearson, 1998. "Using Value-at-Risk to Control Risk Taking: How Wrong Can you Be?," Finance 9810002, EconWPA.
  9. 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).
  10. 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.
  11. Lima, Luiz Renato Regis de Oliveira & Neri, Breno de Andrade Pinheiro, 2006. "Comparing Value-at-Risk Methodologies," Economics Working Papers (Ensaios Economicos da EPGE) 629, Graduate School of Economics, Getulio Vargas Foundation (Brazil).
  12. Mark R. Manfredo. & Raymond M. Leuthold, 1999. "Market Risk Measurement and the Cattle Feeding Margin: An Application of Value-at-Risk," Finance 9908002, EconWPA.
  13. 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.
  14. 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.
  15. 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.
  16. Stephanos Papadamou & George Stephanides, 2004. "Evaluating the style-based risk model for equity mutual funds investing in Europe," Applied Financial Economics, Taylor and Francis Journals, vol. 14(10), pages 751-760.

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