Analysis and Prediction of Stock Based on Chaotic Neural Networks
Ding Hua-fu · Computer Technology and Development · 2009
The chaotic dynamics theory has provided an analytic method to stock price volatility in the stock market.To find out whether the price of stock has the chaotic behavior,has analyzed nonlinear character of the stock price,based on the close index of stock,from the 19th of Dec in 1990 to 24th of Apr in 2008,and have reconstructed the strange attractor of the time sequence by the method of reconstructing phase space,have calculated correlated dimension,and have proved that the exponent of Lyapunov is positive,then affirmed that the chaotic behavior does exit in the time sequence of stock.The neural network is a nonlinear system,it can approach the nonlinear function by learning,by using the neural network,can forecast the stock's direction of the next day.