The Application Of Securities Investment And Analysis Based On Data Mining

The securities market is an important part of our national economy. The stability of securities markets is not only related to national economic prosperity, but also related to the interests of the investors in the stock market. So the validity on the trend of the mark index and stock's analysis and research has important theoretical and practical value. But the securities market has the highly nonlinear characteristics, so a large number of security analysis methods and its application are not satisfactory. Artificial neural network model based data mining has strong non-linear simulation, adaptive and self learning, and the gray system theory has "partial information known and partial information unknown" and "small sample'," poor information "and so on. Therefore, this thesis will use neural network technology and gray system theory to study the trend of market trend and stock deeply.With the help of artificial neural network's approximation ability of nonlinear function, set up BP artificial neural network prediction model for the Shanghai Composite Index, confirm that BP artificial neural network algorithm in the securities investment analysis is effective and feasible. Use the weekly stock closing price on wrapping band with the gray system theory in this article, to predict what will be the stock ranges next week. From which we can see gray system theory model is also very effective in forecasting the stock, it is also significant for the majority of investors.