Applying data mining techniques to stock market analysis

Abstract

The stock market can be viewed as a particular data mining and artificial intelligence problem. The movement in the stock exchange depends on capital gains and losses and most people consider the stock market erratic and unpredictable. However, patterns that allow the prediction of some movements can be found. Stock market analysis deals with the study of these patterns. It uses different techniques and strategies, mostly automatic that trigger buying and selling orders depending on different decision making algorithms. It can be considered as an intelligent treatment of past and present financial data in order to predict the stock market future behavior. Therefore it can be viewed as an artificial intelligence problem in the data mining field. This paper aims to study, construct and evaluate these investment strategies in order to predict future stock exchanges. Firstly, data mining techniques will be used to evaluate past stock prices and acquire useful knowledge through the calculation of some financial indicators. Next artificial intelligence strategies will be used to construct decision making trees.