Providing a Logistic Model to Predict Individual Trading Behavior in Tehran Stock Exchange

Document Type: Original Article

Authors

1 Ph.D. Candidate, Department of Accounting, Faculty of Literature & Human Sciences, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

2 Assistant Prof., Department of Accounting, Faculty of Literature & Human Sciences, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

3 Assistant Prof., Department of Economics, Faculty of Literature and Human Sciences, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

Abstract

Information is like a strategic decision-making tool in which the quality of decisions will merely depend on the information used at the time of making those decisions. The purpose of this research is to assist individual investors in Tehran Stock Exchange by providing them a logistic model enabling them to predict their trading behavior. The data in this research has been collected from the statistical population of the study through variables, believed to have effects on the investors' process of decision making. Therefore, in order to achieve the statistical data, 2400 transactions in the form of 100 transactions, including buy and sell of stock shares from March 2017 until February 2019 have respectively been collected as samples. Based on the results of the logistic regression test, the behavior of institutional investors, as well as the volume of stocks traded have a significant positive impact on the behavior of individual investors (the probability of buying shares by them) versus the Beta, earnings per share, and dividends per share that have a negative effect on the probability of purchasing shares by individual investors. The analysis of the results suggests that individual investors are mainly subject to collective behavior which in particular is the same behavior of institutional investors. On the other hand, they tend to invest in stocks with low beta (defensive stocks) along with factors such as earnings per share and dividends per share which have less impact on the probability of stock purchases by individual investors.

Keywords


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