Investigating Time Varying Herd Behavior in Tehran Stock Exchange: Generalized Autoregressive Score Approach

Herd behavior is one of the most important behavioral biases in financial markets and is one of the determinants of financial crises. Given that herd behavior directly affects price, presenting a model based solely on past prices, with good predictability, indicates the existence of market herd behavior. This article aims to investigate the existence of herd behavior in Tehran Stock Exchange and presents a new nonlinear variable time model called Generalized Autoregressive Score (GAS) and has been compared with traditional GARCH and AR nonlinear models. in order to predict the distribution of return of the total index of the stock exchange during the period 2010 to 2020. The results of modeling for the asset by the new GAS model are compared with the results of the GARCH and AR models and their performance is tested for inside and outside the sample. ample in the internal and external tests show that the new GAS model is more accurate than the traditional GARCH and AR models in predicting the daily return distribution of the total index of the Tehran Stock Exchange and also the presence of herd behavior in Iran's capital market has been approved.