Based On State Transition Asymmetric Pgarch Class Model On The Chinese Stock Market Volatility

The finance market is alawys changeable, especially, chinese finance market is still in continuing adjustment and shunt. Actually, the changeable economic policies and the data structure of financial market are existance. Therefore, it is necessary for the study of financial volability to adopt variable structure model. The research of variable structure model becomes one of the hotspot in finacial volability models. Accordingly, this paper tries to demonstrate that the variable structure model is better than others theoretically, which reflects the Chinese stock market volability. By Empirical Study, we find that the variable structure model is fit to Chinese stock market.In order to reflect the fact, some events should be taken into account in this model, such as the international financial crisis, the release of economic policies, etc. Especially, the volability of the market may be getting more intensity due to the unintegrability of the Chinese market.Consequently, it is very difficult to discribe the volability of the financial market. Many analysis on financial market volatility had been done by domestic and overseas scholars, and built many kinds of volatility models. In general, volatility models are classified to two categories:one is ARCH models ,the other is SV models. Because of the well-satisfied Statistical Characteristics and it's accuracy, ARCH models are applied extensivly to the stuy of Financial vobility. Common models are EGARCH model, TGARCH model, APGARCH model, etc. This paper will introduce a new method,which is called the Regime-Switching APGARCH model, to study volatility.This model, in fact, is an improved APGARCH model, which introduced a two-states Markov switching process. And the volatility are divide into two different states in this model, one state corresponds to the stock market in falling, the other corresponds to the stock market in increasing. And the switching between the two states is controlled by Stochastic Process. Mainly,it improves the RS-GARCH models by including an asymmertic response to news and by allowing the power transformations of the heterokedasticity equations to be estimated directly from the data . Mainly,it improves the RS-GARCH models by including an asymmertic response to news and by allowing the power transformations of the heterokedasticity equations to be estimated directly from the data . Several mixture models ,including classical GARCH model,APGARCH model,RS-GARCH model and RS-APGARCH model,are applied to daily returns time series in China stock market,and the empirical results of the Several mixture models are compared to prove that RS-APGARCH model is better model for volability.By the structure of data may be caused by the release of economic policies,we think the data structure may be influenced by many factors, such as the change of Financial Supervision System, the improvement of financial market itself and the shock of International Financial Crisis. Which makes the existence of the variable structure in conditional vary. Therefore, the variable structure model can well describe the viability of Chinese stock market.Accordingly, because of the great shock and bad stability of the chinese stock market, The varible structure model is fit to the research of the macket volability. it is benefit to the government to make new economic policy, to manage the financial supervise system, and to guide the investigators to avoid the impacat of international financial crisis. At the same time, the government should pay more attention to the construction of the financial market and the education of the investigators. And the government should introduce theshort-mechanism,to enhance the stability of the market and reduce the influentce of the crisis to the stock market.