The volatility of Chinese stock market is investigated using the dynamic version of stochastic volatility model , and Bayesian analysis based on MCMC is introduced to improve the parameters estimation in stochastic volatility model . Empirical results on Chinese stock market indicate that stochastic volatility model outperforms the ARCH model in capturing the heteroskedasticity and serial correlation of volatility of the stock market returns