DETERMINATION STOCK INVESTMENT STRATEGIES OF LISTED COMPANIES IN IRAN USING DATA MINING TECHNIQUES

Hamide Ramezani Aval Riabe (), Mohammad Hossin Vadeei () and Mehrdad Jalali ()
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Hamide Ramezani Aval Riabe: Islamic Azad University, Mashhad, Iran
Mohammad Hossin Vadeei: Associate Professor, Department of Accounting Ferdowsi University of Mashhad, Iran
Mehrdad Jalali: Assistant Professor, Faculty of Engineering, Mashhad Branch Islamic Azad University, Mashhad, Iran

Far East Journal of Psychology and Business, 2012, vol. 8 No 3 Paper 2 September, issue 2, 12-26

Abstract: Investment can be considered as a one of the fundamental pillars of national economy. The single and most important reason is to earn returns on investment. At the present time, many investors look to find a criterion for comparison stock together and selecting the best. The investors try in choosing the type of strategy, to choose strategies that maximize the earning value of the investment process. The current study aims to forecasting stock returns using data mining techniques and determinat return rate of value or growth stocks of listed companies in Tehran Stock Exchange during 2005-2010. The results indicate that the developed model has appointed the investment companies with high accuracy and portfolio value in some years and growth portfolio in some other years has a higher rate of return. It is clear that if it is used hybrid model, rates of return can be increased and the approach presented in this paper is flexible and strong.

Keywords: Investment Strategy; Decision Trees; Clustering; SVM; Discriminant Analysis. (search for similar items in EconPapers)
JEL-codes: M1 (search for similar items in EconPapers)
Date: 2012
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