Risks Of Dependency In The Chinese Stock Market

The motivation of financial risk is the loss or gain of the financial assets caused by many uncertainties changes for an implied risk factor. The development of financial institutions is subject to many risks in the restrictions. In order to better predict and control the risk, the researchers and financial institutions design a number of risk measurement methods, in which VaR is used most often. However, based on the assumption that the gains of a single capital are normal, the income linear dependent calculation of VaR in the risk assets does not match the actual situation. The emergence and application of Copula theory for risk analysis and multivariable time series analysis provide a new direction. Copula is used to describe the correlation in financial market structure, not only can choose a better description of the gains of risk capital distribution function, but also can strip out the correlation in financial market structure, more fully describe the level of dependencies in the risk assets.In this paper, Copula theory is introduced. Because single Copula function can not describe the complex and volatile financial markets comprehensively, we give more suitable Copula model with variability and change structure, which describe the risk assets of stock market. Using Shanghai Stock Index and Shenzhen Composite Stock Index (September 11, 2001 to November 30, 2007) ,we make a empirical analysis about mixed Copula model and a single model applying the VaR calculation. The result show that mixed Copula is better than a single Copula group to simulate the dependence of the risk assets.Tail dependence can be used to describe interaction in assets when the extreme events arise. The past empirical studies show that, under the normal circumstances, the tail dependence is stronger in the declined substantially period of the market, but in the period of rising market, it is weaker. Therefore the research of the tail dependence is very important to understand and control of the major risk of the stock market. This paper also makes a more systematic exposition, and gives a variable structure Copula model with a stronger tail dependence.