Journal of Intelligent Financial Management

Journal of Intelligent Financial Management

Presenting a hierarchical model of the effects of herding beta with an approach to explaining anomalies in the Tehran Stock Exchange

Document Type : Original Article

Authors
1 Department of Financial Engineering, Ya.C., Islamic Azad University, Yazd, Iran
2 Department of Financial Engineering, Ya.C., Islamic Azad University, Yazd, Iran (Corresponding Author)
Abstract
Herding behavior is usually considered a negative phenomenon. Because, when investors imitate each other, purchases and sales are not made based on new and reliable information about the company, but rather on the behavior of others. Herding beta is a driving force in which emotions and collective imitation take logic from the market and cause prices to follow crowd psychology instead of moving based on economic realities, and price anomalies occur. The purpose of the present study was to present a hierarchical model of the effects of herding beta with an approach to explaining anomalies in the Tehran Stock Exchange. The method of this research is mixed (qualitative-quantitative). The qualitative part of the research was conducted by interviewing 21 experts and analyzing the resulting data using the content analysis method (theme), and 19 effective herd beta effects in explaining stock market anomalies were identified and extracted. Then, in the quantitative part, the combined DEMATEL-ISM method was used to design the model. In the DEMATEL part, the relationship and effectiveness of the extracted effects were collected with the help of experts. The collected data were analyzed in the form of a self-interaction matrix using ISM Matlab software, and a four-level model was obtained. The data required for this part was also collected using the self-interaction matrix. Analysis of the collected data with Matlab software led to the formation of four levels, and increasing the level of uncertainty in the stock market was the most effective effect of herd beta on stock market anomalies in this model.
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