A New Algorithm of Neural Network and Prediction in China Stock Market

Artificial neural network is a nonlinear dynamic system, which can attain the reflection of nonlinear relations among variables within any precision, possessing the ability of solving nonlinear problems, therefore also meeting requirements of economic forecasting. Taking advantages of the nonlinear and dynamic characteristics, by adjusting weights, we can approach any continuous functions by enough precision, therefore being able to approach the function in which the stock price changes with time, so we can imitate and learn the trading model of stock market. However, the traditional BP algorithm has low convergent speed. By proposing the deviation rate, this paper improves the convergent speed and it is tested in the forecasting of stock market.