To capture the asymmetric effects of positive shocks(good news)and negative shocks(bad news)to asset returns，this paper incorporates both the threshold and state-dependent leverage effects into the basic stochastic volatility (SV) model，and proposes a threshold SV model with double leverage(THSV-DL)to model the volatility of asset returns．Based on the efficient importance sampling(EIS) technique，we use the maximum likelihood(ML)method to estimate the parameters of the THSV-DL model．Then，Monte Carlo simulations are presented to examine the accuracy and small sample properties of the proposed method．The experimental results show that the EIS-ML method performs very well．We apply the THSV-DL model to the daily returns of Shanghai stock exchange(SSE)composite index and Shenzhen stock exchange(SZSE)component index of China．Empirical results show that there exists a high persistence of volatility and a significant leverage effect in China’s stock market．More importantly，asymmetries in the volatility persistence，volatility of volatility and leverage effect are discovered in China’s stock market．Specifically，the volatility persistence tends to be higher，and both volatility of volatility and leverage effect tend to be lower following the bad news than following the good news．Finally，an empirical study on the accuracy of value at risk(VaR)estimates based on Shanghai stock exchange composite index is presented．The empirical results demonstrate that the THSV-DL model can yield more balanced and accurate VaR estimates than the basic SV，SV with leverage effect (SV-L)，THSV，and THSV with leverage effect (THSV-L) models．