Ranking the predictive performances of value-at-risk estimation methods
We introduce a ranking model and a complementary predictive ability test statistic to investigate the forecasting performances of different Value at Risk (VaR) methods, without specifying a fixed benchmark method. The period including the recent credit crisis offers a unique laboratory for the analysis of the relative successes of different VaR methods when used in both emerging and developed markets. The proposed ranking model aims to form a unified framework which penalizes not only the magnitudes of errors between realized and predicted losses, but also the autocorrelation between the errors. The model also penalizes excessive capital allocations. In this respect, the ranking model seeks for VaR methods which can capture the delicate balance between the minimum governmental regulations for financial sustainability, and cost-efficient risk management for economic vitality. As a complimentary statistical tool for the ranking model, we introduce a predictive ability test which does not require the selection of a benchmark method. This statistic, which compares all methods simultaneously, is an alternative to existing predictive ability tests, which compare forecasting methods two at a time. We test and rank twelve different popular VaR methods on the equity indices of eleven emerging and seven developed markets. According to the ranking model and the predictive ability test, our empirical findings suggest that asymmetric methods, such as CAViaR Asymmetric and EGARCH, generate the best performing VaR forecasts. This indicates that the performance of VaR methods does not depend entirely on whether they are parametric, non-parametric, semi-parametric or hybrid; but rather on whether they can model the asymmetry of the underlying data effectively or not.
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- Giacomini, Raffaella & White, Halbert, 2003.
"Tests of Conditional Predictive Ability,"
University of California at San Diego, Economics Working Paper Series
qt5jk0j5jh, Department of Economics, UC San Diego.
- David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
- John Y. Campbell & Ludger Hentschel, 1991.
"No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns,"
NBER Working Papers
3742, National Bureau of Economic Research, Inc.
- Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
- Hentschel, Ludger & Campbell, John, 1992. "No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns," Scholarly Articles 3220232, Harvard University Department of Economics.
- Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
- Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
- Francis X. Diebold & Robert S. Mariano, 1994.
"Comparing Predictive Accuracy,"
NBER Technical Working Papers
0169, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
- Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
- Kenneth D. West, 1994.
"Asymptotic Inference About Predictive Ability,"
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Robert F. Engle & Simone Manganelli, 2004.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 22, pages 367-381, October.
- Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- 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.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
- Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
- Peter Christoffersen, 2004.
"Backtesting Value-at-Risk: A Duration-Based Approach,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 2(1), pages 84-108.
- Peter Christoffersen & Denis Pelletier, 2003. "Backtesting Value-at-Risk: A Duration-Based Approach," CIRANO Working Papers 2003s-05, CIRANO.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993.
" On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,"
Journal of Finance,
American Finance Association, vol. 48(5), pages 1779-1801, December.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- Francis X. Diebold & Jose A. Lopez, 1995.
"Forecast evaluation and combination,"
9525, Federal Reserve Bank of New York.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
- Hentschel, Ludger, 1995. "All in the family Nesting symmetric and asymmetric GARCH models," Journal of Financial Economics, Elsevier, vol. 39(1), pages 71-104, September.
- Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 53-89.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Hung, Jui-Cheng & Lee, Ming-Chih & Liu, Hung-Chun, 2008. "Estimation of value-at-risk for energy commodities via fat-tailed GARCH models," Energy Economics, Elsevier, vol. 30(3), pages 1173-1191, May.
- Jon DANIELSSON & Casper G. DE VRIES, 2000. "Value-at-Risk and Extreme Returns," Annales d'Economie et de Statistique, ENSAE, issue 60, pages 239-270.
- Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
- McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
- 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, 06.
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