Prediction of Stock Market Index based on Neural Networks, Genetic Algorithms, and Data Mining Using SVD

Nowadays, most of the investors are interested to use the predicting tools for obtaining the accurate information about the stock market indices and to make a wise decision based on the precise market price. The prediction of the stock market index is an attractive research area that needs to be done with especial tools and with accurate algorithms. In this research we have used the Neural Network (NN) for the learning and curve fitting process, Genetics Algorithm (GA) for the path search and optimization process , Decision Tree and Data Mining, using SVD to obtain the maxim accuracy of the prediction. The maximum accuracy of the prediction rate obtained for DJIA by using machine learning techniques is about 77.8%. Our focus on this research is to improve the decision tree, data mining and neural network techniques by using the Eigen System Analysis, Mean value, and SVD.