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Forecasting Value-at-Risk Using the Markov-Switching ARCH Model

  • Wei-Ting Tang
  • Yin-Feng Gau

This paper analyzes the application of the Markov-switching ARCH model (Hamilton and Susmel, 1994) in improving value-at-risk (VaR) forecast. By considering a mixture of normal distributions with varying variances over different time and regimes, we find that the “spurious high persistence†found in the GARCH model is adjusted. Under relative performance and hypothesis-testing evaluations, the VaR forecasts derived from the Markov-switching ARCH model are preferred to alternative parametric and nonparametric VaR models that only consider time-varying volatility. JEL classification: C22, C52, G28. Keywords: Value-at-Risk, Switching-regime ARCH models.

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File URL: http://repec.org/esFEAM04/up.25992.1080729039.pdf
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Paper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 715.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:feam04:715
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  1. 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.
  2. Andrew Ang & Geert Bekaert, 1998. "Regime Switches in Interest Rates," NBER Working Papers 6508, National Bureau of Economic Research, Inc.
  3. 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.
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