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Empirical analysis of GARCH models in value at risk estimation

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  • So, Mike K.P.
  • Yu, Philip L.H.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Financial Markets, Institutions and Money.

Volume (Year): 16 (2006)
Issue (Month): 2 (April)
Pages: 180-197

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Handle: RePEc:eee:intfin:v:16:y:2006:i:2:p:180-197

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Web page: http://www.elsevier.com/locate/intfin

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  1. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  2. Beltratti, Andrea & Morana, Claudio, 1999. "Computing value at risk with high frequency data," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 431-455, December.
  3. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-94, October-D.
  4. Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, 02.
  5. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  6. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
  7. Vilasuso, Jon, 2002. "Forecasting exchange rate volatility," Economics Letters, Elsevier, vol. 76(1), pages 59-64, June.
  8. Balaban, Ercan, 2004. "Comparative forecasting performance of symmetric and asymmetric conditional volatility models of an exchange rate," Economics Letters, Elsevier, vol. 83(1), pages 99-105, April.
  9. 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.
  10. Mike So, 2000. "Long-term memory in stock market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 519-524.
  11. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  12. 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.
  13. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
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Cited by:
  1. Victoria Gabriela ANGHELACHE & Dumitru Cristian OANEA & Bogdan ZUGRAVU, 2013. "General Aspects Regarding the Methodology for Prediction Risk," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(2), pages 66-72, May.
  2. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Cheng-Few Lee & Jung-Bin Su, 2012. "Alternative statistical distributions for estimating value-at-risk: theory and evidence," Review of Quantitative Finance and Accounting, Springer, vol. 39(3), pages 309-331, October.
  4. Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014. "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 59-85.
  5. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.
  6. 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.
  7. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
  8. 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.
  9. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
  10. McMillan, David G. & Kambouroudis, Dimos, 2009. "Are RiskMetrics forecasts good enough? Evidence from 31 stock markets," International Review of Financial Analysis, Elsevier, vol. 18(3), pages 117-124, June.
  11. Diamandis, Panayiotis F. & Drakos, Anastassios A. & Kouretas, Georgios P. & Zarangas, Leonidas, 2011. "Value-at-risk for long and short trading positions: Evidence from developed and emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 165-176, June.
  12. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
  13. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
  14. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
  15. 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.

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