Stock Market Prediction Using Artificial Neural Networks...

Stock Market Prediction Using Artificial Neural Networks and Regression Analysis Tyler T. Procko Embry-Riddle Aeronautical University TO: Professor Michael Perez, M.A., M.F.A. FROM: Tyler T. Procko DATE: 10/03/2016 SUBJECT: Analytical Report Proposal I. Purpose / Background / Audience: Relatively accurate prediction of multi-tiered, non-linear events has long been a difficult and time-consuming task to perform; forecasting the movement of securities on the stock market included. Stock prices fluctuate for innumerable reasons, so correctly forecasting a stock’s movement can be extremely difficult. There are two areas that have massive effect on stock pricing: the psychology, or sentiment of investors and the mathematical, or analytical standpoint. In order to effectively predict stock price movement, these two areas, more than anything else, must be factored in. Fundamental and technical analysis are easily included, but accounting for investor sentiment is more complicated. Using artificial neural networks (ANNs) coupled with the two schools of traditional analysis and regression analysis could prove useful in correctly forecasting the price movement of stocks on any exchange. How can ANNs be implemented with regressi on analysis to accurately predict the movement of stock prices? This report will be a semi-technical feasibility analysis of the different types of ANNs, predictive algorithms and financial analysisShow MoreRelatedStock Prices Prediction Using Artificial Neural Networks7197 Words   |  29 PagesStock Prices prediction using Artificial Neural Networks Ajay Kamat Flat 2, Jaysagar 2, Navy Colony Liberty Garden, Malad west, Mumbai – 400064 +919833796261 ajay1185@gmail.com ABSTRACT The aim of this research paper is to facilitate prediction of the closing price of a particular stock for a given day. A thorough analysis of the existing models for stock market behavior and different techniques to predict stock prices was carried out. 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