2017 The 5th International Symposium on Project Management (ISPM 2017)

104 / 2017-05-25 08:51:22

High Embedded Dimension Stock Data Prediction Model Based on Chaotic Prediction Model

1909,2203,Shanghai Composite Index,Time delay,Lyapunov exponent

A correct understanding of the stock market volatility and its forecast for the stable development of China's stock market is under a very important significance. In a fully defined system produced a very complex movement changes, which called chaos. The research shows that there are chaotic characteristics in the stock market, and the Chinese stock market has a chaotic system with fractal dimension structure. The primary goal of this research is tantamount to predict the volatility of the stock market. This paper uses one-rank local-region method and the Lyapunov exponent prediction model which are based on Chaotic Prediction Model. The phase space is constructed according to the characteristics of the Lyapunov index, and the Shanghai Composite Index is predicted based on the maximum Lyapunov exponents.