Modeling of Noise Trading Effect on Extreme Return Based on Quantile Regression Approach

Noise traders have an undeniable role in determining market volatility, returns and stock price movements. Therefore, In this paper, the effect of noise traders on the stock returns of companies with the aim of presenting an appropriate picture of how they are affected in extreme situations.The statistical population of this study includes all companies listed in Tehran Stock Exchange during the period of 2009-2017. The sample of 13717 data from 150 companies listed on the stock exchange monthly. The main hypothesis of this study is to evaluate the Extreme Effects of noise trading on stock returns by quantile regression was used to analyze the data. The findings of the research show that the level of noise activity increases with the level of efficiency Moreover,the positive effect of the noise trading index on returns with a coefficient of 0.0001.Under extreme returns, this effect is greater than the intermediate values and reflects the intensification of noise trading activity in periods of decline and market growth.