Using Copula Models To Investigate The Structure Of Dependence In China Stock Markets On The Basis Of Special Algorithm

The Graduation thesis describes the Correlation between different china industry stock market through Copula Model, which analysis the risk of trade stock, and using advanced algorithm to solve the problem that how to describe Correlation between different china industry stock market. The research approaches include Normal distribution, Copula thesis, GARCH model, Fitness Test, Genetic Algorithm. Copula function include several models, such as Gumbel, Claton , Frank. In this dissertation, copula theory and its applications in multivariate financial time series analysis are studied intensively. As a result of those researches, several multivariate financial time series models based on copula theory are proposed. Methods of constructing dynamic models and applications of copula models in financial risk management are also investigated systematically. And then we support algorithm to solve the problem that how to describe Correlation between different china industry stock market. The key points and main achievements of this work are listed as follows:Using the proper procedures and genetic algorithm to solve the problem that how to describe Correlation between different china industry stock market.