Identifying the Trading Behaviors and Risk of Noise Traders in Iran Stock Market

Generally, it is believed that disrupted trades would cause market failure, and understanding the causes of inefficiencies     has always been a real challenge in financial literature.In this regard, the present study investigates the existence of noise traders in Iran stock market and tests a quantify model for measuring noise trader risk, overreaction, underreaction and mispricing. For the first time, the most viewed stocks were used to construct a behavioral index. This new index can be used to identify noise traders and applying this index can be obtained more accurate estimate of the beta in compared with market index. Also by using CAPM and BAPM models during the period from 2011 to 2016 for 96 companies, it was shown that Iran stock market has a significant behavior error. Furthermore, the results of information-adjusted noise model (IANM) show that noise traders are active 100 per cent of the time on the Iran stock market and make it inefficient. The most type of inefficiency in this market is overreaction in 46.67 percent of the time and then information pricing errors and under reaction are in 45.63 percent and 7.71 percent of the time, respectively. The findings of this study are useful for understanding the market atmosphere and new behavioral index can be used as a proxy of Iranian investors` sentiment.