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.
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Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE J-Series with number
CIRJE-J-191.