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Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-

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  • Tsunehiro Ishihara

    (Graduate School of Economics, University of Tokyo)

  • Yasuhiro Omori

    (Faculty of Economics, University of Tokyo)

Abstract

The stochastic volatility model has been popular to explain a dynamic structure of financial time series such asset returns. In this paper, we first consider the asymmetry that the increase in the volatility is followed by the decrease in the asset return. Then, we consider a Markov switching of two (high and low) volatility states using a random state variable which follows a Markov process. The restrictions for the identification of the switching parameters are determined by using a permutation sampler with Markov chain Monte Carlo method. The Markov switching asymmetric stochastic volatility model is applied to TOPIX returns data, and model comparisons are conducted.

Suggested Citation

  • Tsunehiro Ishihara & Yasuhiro Omori, 2008. "Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-," CARF J-Series CARF-J-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:jseres:cj045
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    File URL: http://www.carf.e.u-tokyo.ac.jp/pdf/workingpaper/jseries/46.pdf
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    Cited by:

    1. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.

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