Evaluating the Herding Effect on Idiosyncratic Volatility in the Industries of the Tehran Stock Exchange

This study investigates, for the first time,the herding behavior effect on the excessive market idiosyncratic volatility in the industries listed on the Tehran Stock Exchange. We use daily data of 105 firms in 21 industries for the period 2008 to 2020, which covers the stock price bubbles and nuclear sanctions against Iran. The result sof the modified cross-sectional absolute deviation(CSAD) model show that during such turmoil periods, herding does not exist in the whole market, but is observed in eight industries. Moreover, because of the fear of larg elosses during market turmoil, investors ignore their own information to imitate the decisions of in form edtraders, and, in turn, herding in thirteen industries. Moreover, the findings of the modified GJR-GARCH model highlight that herding has a different effect on volatility across the different industries. In particular, her dingnegatively affect tsthe conditional idiosyncratic volatility in fourteen industries along withthe whole market. Furthermore, because the larger trading volume results in higher informed trading,trading volume turnover egatively affects the conditional idiosyncratic volatility in sixteenin dustries.