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

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  • Wei-Ting Tang
  • Yin-Feng Gau

Abstract

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.

Suggested Citation

  • Wei-Ting Tang & Yin-Feng Gau, 2004. "Forecasting Value-at-Risk Using the Markov-Switching ARCH Model," Econometric Society 2004 Far Eastern Meetings 715, Econometric Society.
    • Handle: RePEc:ecm:feam04:715
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    4. 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.
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    More about this item

    Keywords

    Value-at-Risk; Switching-regime ARCH models;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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