Abstract: Based on the superiority and definition of Kendall’s  rank correlation coefficient, this paper puts forward a new Kendall’  Dynamic Conditional Correlated Copula model which is of economic significance. And we construct three kinds of Kendall’s - Dynamic Conditional Correlated Copula model to describe different correlations by applying this new model to Gaussian, Clayton and Gumbel copula. These models not only have fewer parameters and are less time-consuming in calculation, but also overcome the shortcoming of the existing Dynamic Conditional Correlation Copula models that it is not convenient to evaluate because of their different constructing methods. Moreover, this new model can carry out multi-step ahead prediction with less time-consuming in out-of-sample prediction, providing a new approach to characterize the time-varying, nonlinear, non-symmetry, tail dependence and other complicated correlation.

Key words: Dynamic Conditional Correlated Copula model, correlation, Kendall’s