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A Stochastic Volatility Model with Markov Switching

Author

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  • So, Mike K P
  • Lam, K
  • Li, W K

Abstract

This article presents a new way of modeling time-varying volatility. The authors generalize the usual stochastic volatility models to encompass regime-switching properties. The unobserved state variables are governed by a first-order Markov process. Bayesian estimators are constructed by Gibbs sampling. High-, medium-, and low-volatility states are identified for the Standard and Poor's 500 weekly return data. Persistence in volatility is explained by the persistence in the low- and the medium-volatility states. The high-volatility regime is able to capture the 1987 crash and overlap considerably with four U.S. economic recession periods.

Suggested Citation

  • So, Mike K P & Lam, K & Li, W K, 1998. "A Stochastic Volatility Model with Markov Switching," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 244-253, April.
    • Handle: RePEc:bes:jnlbes:v:16:y:1998:i:2:p:244-53
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