Stock Analyse And Its Logical Design Based On Artificial Neural Network

High income with high risk is the character of the stock market. At all times investors work hardly to grope after the rule of the stock market for gainning the earnings and avoiding the loss. In the lately years, the development of the computer technology and artificial intelligence provides with the favorable environment to scientific analyze the stock market and measure stock value for the investors. The thesis starts to research the stock market with neural network technology under the ground of these conditions.Firstly, the article clarifies the traditional theory of the stock analyse with its merits and demerits. And then ,the article clarifies the basic theory of the neural network which points out the merit of using neural network to analyze the stock market.Secondly, in the article the neural stock analyse model has been constituted .The model is made of three parts: index system based on the finance report data synchronous dada of the stock market and the macro-economy data of the country; the choice of the arithmetic model; output of the model.Thirdly, according to the model idea, the thesis emphatically discusses the key questions such as the system function, the system data flow diagram. And these finally build the favorable foundation to realize the model.Finally, the thesis makes the positive analyse with the real stock data of Pufa, Minsheng, Aijian. The results of the positive analyse demonstrates that the neural stock analyse model that established in the thesis has the sectional theory value and application value.