Abstract: As financial time series have the characteristics of dynamic time-varying, asymmetric and nonlinear correlation, the article presented a mixture Copula model which had time-varying weight coefficients and Copula parameters. Meanwhile, based on mixture Copula models whose weight coefficients and Copula parameters were both time-varying, to describe the correlation between different frequency of internet banking stocks price series, then we construct a new kind of pairs trading strategy model, and compared with that of static mixture Copula models. Empirical analysis shows that pairs trading strategy based on time-varying mixture Copula models gains a high stable returns. Both of weight coefficients and Copula parameters are time-varying can capture more trade opportunities and strategy performance is the best. Mixture Copula models which have more Copula functions don’t have the advantage in pairs trading strategy. High frequency financial markets are more profitable than the corresponding low frequency financial markets.