Explanation of the Role of Investors’ Emotional Inclination on the Stock Liquidity of Firms Listed on Tehran Stock Exchange

Subject Areas : Journal of Investment Knowledge

hamid moridipour ¹ , Mahmoud Hemmatfar ² , mohammad hasan janani ³

1 - phd of Student, Department of Accounting, Boroujerd Branch, Islamic Azad University, Boroujerd Iran.
2 - Associate of Prof. Department of Accounting, Boroujerd Branch, Islamic Azad University, Boroujerd Iran
3 - Assistant of Prof. Department of Accounting, Boroujerd Branch, Islamic Azad University, Boroujerd Iran.

Received: 2021-06-27 Accepted : 2021-09-06 Published : 2022-06-22

Keywords: Financial-Behavioral Approach, Classical Financial Theories, Investors’ Emotional Features, stock liquidity,

Abstract :

Many studies introduce the liquidity of assets, one of the variables considered by investors, to be influenced by various factors such as investors’ emotions. The investors’ emotions in the market are explained by the financial behavioral approach. This approach is the opposite of the classical financial theories. Hence, this study was mainly aimed at investigating the relationship between investors’ emotional features and the stock liquidity in the Iranian stock market. To this end, the data of 95 active firms from those listed in stock exchange market in a 7-year period from 2013 to 2019 (Solar Years 1392-1398) were investigated using a multivariate regression model based on the panel data method. The results of testing the research hypotheses revealed a significant relationship between the investors’ emotional features and the stock liquidity of large and small firms. Given the significance level of the research model’s modulators, the high and low emotional features in small firms have a significant negative relationship with stock liquidity; however, this significant relationship was not confirmed for large firms. Furthermore, the significance of the whole regression model may be concluded given F statistic. Based on Durbin-Watson statistics, there is no strong autocorrelation between the research variables.

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