Stochastic Volatility Models Based Bayesian Method and Their Application

Stochastic volatility(SV) models here are investigated based on bayesian method,and are applied to estimate and forcast the Value at Risk(VaR) of the Chinese stock market.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.VaR based on SV models is more precision than that based on GARCH models.