A robust VaR model under different time periods and weighting schemes
AbstractThis paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable. Copyright Springer Science+Business Media, LLC 2007
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Bibliographic InfoArticle provided by Springer in its journal Review of Quantitative Finance and Accounting.
Volume (Year): 28 (2007)
Issue (Month): 2 (February)
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Web page: http://springerlink.metapress.com/link.asp?id=102990
Asymmetric power ARCH; Backtesting; Extreme value theory; Filtered historical simulation; Value-at-risk;
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- Ho, Lan-Chih & Burridge, Peter & Cadle, John & Theobald, Michael, 2000. "Value-at-risk: Applying the extreme value approach to Asian markets in the recent financial turmoil," Pacific-Basin Finance Journal, Elsevier, vol. 8(2), pages 249-275, May.
- Gita Persand & Chris Brooks, 2003. "Volatility forecasting for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 1-22.
- Pierre Giot & Sébastien Laurent, 2003.
"Value-at-risk for long and short trading positions,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
- GIOT, Pierre & LAURENT, Sébastien, 2001. "Value-at-risk for long and short trading positions," CORE Discussion Papers 2001022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Pierre Giot and S»bastien Laurent, 2001. "Value-At-Risk For Long And Short Trading Positions," Computing in Economics and Finance 2001 94, Society for Computational Economics.
- Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2000. "Diagnosing and treating the fat tails in financial returns data," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 389-416, November.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- GIOT, Pierre & LAURENT, Sébastien, 2003.
"Market risk in commodity markets: a VaR approach,"
CORE Discussion Papers
2003028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Vlaar, Peter J. G., 2000. "Value at risk models for Dutch bond portfolios," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1131-1154, July.
- 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.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Jondeau, Eric & Rockinger, Michael, 2003.
"Testing for differences in the tails of stock-market returns,"
Journal of Empirical Finance,
Elsevier, vol. 10(5), pages 559-581, December.
- ROCKINGER, Michael & JONDEAU, Eric, 2001. "Testing for differences in the tails of stock-market returns," Les Cahiers de Recherche 739, HEC Paris.
- ROCKINGER, Michael & JONDEAU, Eric, 1999.
"The Tail Behavior of Stock Returns: Emerging versus Mature Markets,"
Les Cahiers de Recherche
668, HEC Paris.
- Jondeau, E. & Rockinger, M., 1999. "The Tail Behavior of Sotck Returns: Emerging Versus Mature Markets," Working papers 66, Banque de France.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
- R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor and Francis Journals, vol. 1(2), pages 237-245.
- 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.
- Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998.
"Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management,"
New York University, Leonard N. Stern School Finance Department Working Paper Seires
98-081, New York University, Leonard N. Stern School of Business-.
- Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," Center for Financial Institutions Working Papers 98-10, Wharton School Center for Financial Institutions, University of Pennsylvania.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999.
"Value-at-Risk analysis of stock returns: Historical simulation, varinace techniques or tail index estimation ?,"
WO Research Memoranda (discontinued)
579, Netherlands Central Bank, Research Department.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999. "Value-at-Risk Analysis of Stock Returns Historical Simulation,Variance Techniques or Tail Index Estimation?," DNB Staff Reports (discontinued) 40, Netherlands Central Bank.
- Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
- Billio, Monica & Pelizzon, Loriana, 2000. "Value-at-Risk: a multivariate switching regime approach," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 531-554, December.
- Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2010. "The Use of GARCH Models in VaR Estimation," Working Papers 0048, University of Peloponnese, Department of Economics.
- Brooks, C. & Clare, A.D. & Dalle Molle, J.W. & Persand, G., 2005. "A comparison of extreme value theory approaches for determining value at risk," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 339-352, March.
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- 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.
- Gencay, Ramazan & Selcuk, Faruk, 2004. "Extreme value theory and Value-at-Risk: Relative performance in emerging markets," International Journal of Forecasting, Elsevier, vol. 20(2), pages 287-303.
- Brooks, Robert D. & Faff, Robert W. & McKenzie, Michael D. & Mitchell, Heather, 2000. "A multi-country study of power ARCH models and national stock market returns," Journal of International Money and Finance, Elsevier, vol. 19(3), pages 377-397, June.
- So, Mike K.P. & Yu, Philip L.H., 2006. "Empirical analysis of GARCH models in value at risk estimation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(2), pages 180-197, April.
- Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
- Gabrielsen, A. & Zagaglia, Paolo & Kirchner, A. & Liu, Z., 2012.
"Forecasting Value-at-Risk with time-varying variance, skewness and kurtosis in an exponential weighted moving average framework,"
39294, University Library of Munich, Germany.
- A. Gabrielsen & P. Zagaglia & A. Kirchner & Z. Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewnessn and Kurtosis in an Exponential Weighted Moving Average Framework," Working Papers wp831, Dipartimento Scienze Economiche, Universita' di Bologna.
- Alexandros Gabrielsen & Paolo Zagaglia & Axel Kirchner & Zhuoshi Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewness and Kurtosis in an Exponential Weighted Moving Average Framework," Working Paper Series 34_12, The Rimini Centre for Economic Analysis.
- A. Gabrielsen & P. Zagaglia & A. Kirchner & Z. Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewness and Kurtosis in an Exponential Weighted Moving Average Framework," Papers 1206.1380, arXiv.org.
- Trenca Ioan & Zoicas-Ienciu Adrian, 2010. "The Correlation Between The Market Risk And The Liquidity Risk In The Romanian Banking Sector," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 437-442, July.
- Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
- Chee Lim & Patricia Tan, 2007. "Value relevance of value-at-risk disclosure," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 353-370, November.
- Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
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