Predicting Stock Exchange Behaviour using Decision Tree and Type Effect Weight (TEW) Algorithm
Abstract
In this paper, various factors are investigated that effect the behavior of Stock exchange share process. The aim is to identify and analyze the effects of factors that are driven through various environmental and political situations in the country which drive the rise and fall of share prizes. Based on the results of these analysis an algorithm is derived using Artificial Intelligence (AI) with Expert System and Rule-Based System, to predict the behavior of stock prices. The system uses decision tree algorithm along with a novel Type, Effect and Weight (TEW) Algorithm, to intelligently predict the pattern of stock prizes. The system predicts the behavior of stock exchange market, forecasting the market rate to either increase or will it decrease using AI (Expert Tasks). The purpose of this work is to facilitate user of stock exchange and save money of investors.
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