Exploring Herding Behavior based on Weighted Cross-Sectional Variance (WCSV) in Tehran Stock Exchange

Herding behavior of investors is one of the main behavioral fears and important biases in financial markets that has attracted a lot of attention. The existence of herding in behavior is a term for explaining how individuals within a group can work together without the prior plan. This research identifies and measures this important bias and examines herding behavior in Tehran Stock Exchange. This study, using a Weighted Cross-Sectional Variance analysis method, which is a new method based on the theory of pricing arbitrage, has been used to identify herding behavior. This is a combination of models based on return dispersion and beta-based models. The statistical population included all companies accepted in the Tehran Stock Exchange during the period of 1389-1394. In this research, the Chang, Chang and Khorana return distribution model and also the CAPM-based cross-sectional variance model are estimated and compared with the original model, which results indicate the superiority of the original model compared to other models. Also, the results of the research indicate that herding behavior is poorly observed in all years, while during the research period of 1392, there are more strong herding points and therefore, more than other years, faced with herding behavior phenomenon.