Intelligent Threshhold Garch Model Applied to Stock Market of Transmissions that Volatility

This paper considers that transmissions of volatility are time-vary and asymmetric. Generally, there are many and complex reasons that can affect transmissions of volatility such as good news and bad news, etc. In this situation, the model estimation is more difficult to solve and becomes a highly nonlinear with many local minima problem. For these reasons, we adopt the method of artificial intelligence to propose an ITGARCH (Intelligent Threshold Generalized Autoregression Conditional Heteroscedasticity) model. In this paper, we would modify the threshold value by using the rule of intelligent. The ITGARCH model, which combines the advantages of the GA (Genetic Algorithm) and Fuzzy theory to describing time-vary and asymmetric properties of volatility. The results indicate the transmission of volatility for stock markets are time- vary nonlinear and asymmetric. The transmissions of volatility in propose model is exactly performance.