This paper constructs stochastic Copula models to study the time-varying leverage effects in Chinese stock markets at the extremes． It is well-known that volatility can not be directly observed in the financial mar-kets． To overcome this problem，realized volatility is used to measure the latent volatility． Then the efficient importance sampling-based maximum likelihood ( EIS-ML) estimation is adopted to estimate the parameters of the stochastic Copula models． The empirical results from data of Shanghai and Shenzhen stock markets demon-strate that the leverage effects in Chinese stock markets exhibit asymmetric features． Specifically，extremely low stock market returns tend to be associated with extremely large volatilities，but extremely high stock market returns are not related to small volatilities． Moreover，the leverage effects in Chinese stock markets are found to be changing over time and exhibit similar variation trends in Shanghai and Shenzhen stock markets． The sto-chastic Copula models are shown to outperform other Copula models，including the static Copula models and time-varying Copula models．