Tail Gradual Characteristic Changes Of Related Research On China’s Stock Market

Since the tail dependence has been analyzed very well, and the classification of copula function is various. Take the upper tail dependence parameter and the lower tail dependence one for example: firstly, choose the best filled copula function, which can be got by the relationship with the Kendall’s tau. This paper is based on the former study, according to the concept of the tail dependence parameter and the conditional probability, to fetch the best fitted function and to describe different tail dependence characters. There are a lot of details, absolutely. Compared with the Kolmogorov-Smirnov(K-S) method and test of goodness of fit, we choose the last one. Then we construct the tail dependent function in different ranges. Here we get the open and closed interval conditional expectation function based on copula. The open interval is the average of the range of the tail part, while the closed one is the average of the chosen range data. The conclusion is some references to the investment strategy and it holds the overall situation.