An Intelligence prediction of stock market analysis using extreme dynamic data mining techniques Predictions

Abstract

Stock market, it’s the place where everyone got interest in making money. But many people think that stock market predictions as gambling but what actually is, stock exchange movements are depends on capital gains and losses. Most people believes that stock exchange movements are unpredictable. But by using extreme data mining techniques on previous stock exchange data we can predict the future stock exchanges. This paper tries to help the investors in the stock market to decide the better timing for buying or selling stocks based on the knowledge extracted from the previous data of such stocks. In this paper we are using decision tree algorithm which is one of the data mining techniques. To build the proposed model, the CRISP-DM methodology is used over real previous data of two major companies.