Stock forecasting using evolutionary neural network

Stock market is complicated dynamic system affected by many factors. To forecast it, many methods have been proposed. But those methods cannot solve this problem very well. In this paper, from analyses the mathematic description of stock market system, a new forecasting method based on new evolutionary neural network is proposed here. In this new evolutionary neural network, the traditional BP algorithm and a new bionics algorithm, immunized evolutionary programming proposed by author is combined. In order to verify this new prediction method, the stock market data of Shanghai market in 1996 is used. The results show that, our new method is very good to real practice.