The Use of GARCH Models in VaR Estimation
AbstractWe evaluate the performance of an extensive family of ARCH models in modelling daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.
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Bibliographic InfoPaper provided by University of Peloponnese, Department of Economics in its series Working Papers with number 0048.
Length: 34 pages
Date of creation: 2010
Date of revision:
Value at Risk; GARCH estimation; Backtesting; Volatility forecasting; Quantile Loss Function.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-28 (All new papers)
- NEP-ECM-2010-03-28 (Econometrics)
- NEP-ETS-2010-03-28 (Econometric Time Series)
- NEP-FOR-2010-03-28 (Forecasting)
- NEP-RMG-2010-03-28 (Risk Management)
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- Med Imen Gallali & Raggad Zahraa, 2012. "Evaluation of VaR models' forecasting performance: the case of oil markets," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 5(3), pages 197-215.
- Javed Iqbal & Sara Azher & Ayesha Ijaz, 2010.
"Predictive Ability of Value-at-Risk Methods: Evidence from the Karachi Stock Exchange-100 Index,"
EERI Research Paper Series
EERI_RP_2010_18, Economics and Econometrics Research Institute (EERI), Brussels.
- Iqbal, Javed & Azher, Sara & Ijza, Ayesha, 2010. "Predictive ability of Value-at-Risk methods: evidence from the Karachi Stock Exchange-100 Index," MPRA Paper 23752, University Library of Munich, Germany.
- Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
- Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1333-1342.
- Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
- Milan Rippel & Ivo Jánský, 2011. "Value at Risk forecasting with the ARMA-GARCH family of models in times of increased volatility," Working Papers IES 2011/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2011.
- BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," CORE Discussion Papers 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- repec:dgr:eureir:1765017295 is not listed on IDEAS
- Maria Rosa Nieto & Esther Ruiz, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," Statistics and Econometrics Working Papers ws087326, Universidad Carlos III, Departamento de Estadística y Econometría.
- Dimitrios P. Louzis & Spyros Xanthopoulos‐Sisinis & Apostolos P. Refenes, 2013.
"The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 32(6), pages 561-576, 09.
- Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
- Sabrina Khanniche, 2009. "Evaluation of Hedge Fund Returns Value at Risk Using GARCH Models," EconomiX Working Papers 2009-46, University of Paris West - Nanterre la Défense, EconomiX.
- Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
- Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
- Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 149-171.
- Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
- Marco Bee & Fabrizio Miorelli, 2010. "Dynamic VaR models and the Peaks over Threshold method for market risk measurement: an empirical investigation during a financial crisis," Department of Economics Working Papers 1009, Department of Economics, University of Trento, Italia.
- repec:ner:carlos:info:hdl:10016/3384 is not listed on IDEAS
- George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
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