The Selection On Copula Model And Its Application In Financial Markets

The financial market is the most active and the most penetrative in the modern market system.It is great practical value to study the dependence structure of different financial markets and explore the dependency structure characteristics of different markets,which will be of great importance to the risk management and risk control of financial markets.The Copula function can be used to deal with the correlation between the variables.In view of the current Copula functional research,the Copula function model choice and its application in financial markets will be concerned on the paper,specific contents:(1)Non-parametric estimation is used to get the distribution function of Copula,then the best-fit Copula is selected by using the squared Euclidean distance.Finally,the paper makes an empirical analysis of the correlation between Shanghai Stock Index and Shenzhen Stock Index.The empirical results indicate the presence of significant correlations between Shanghai and Shenzhen Stock market,and have the high degree of association between them with same rise and fall in a non-extreme market conditions.(2)Single Copula function in the description of the correlation between the variables has some shortcomings,especially in the real financial field,and there are certain limitations.However,the mixed Copula function model can solve this problem to a certain extent.The mixed Copula function with different Copula functions,it can better describe the correlation structure between variables than the single Copula.The mixed copula model made of Gumbel?Clayton and Frank is applied to establish a model of dependence structure between Shanghai Stokes Index and Shenzhen Stokes Index on the paper.EM algorithm is used to calculate the weight and the related parameters of the most difficult solution.The results indicate that the mixed copula model can describe the dependence structure between two markets more accurately,and the dependence relation of upper tail of two markets is stronger than the dependence relation of lower tail.