Revisiting Herding Investment Behavior on the Zagreb Stock Exchange: A Quantile Regression Approach
AbstractHerding investment behavior on stock markets has consequences for practitioners, theorists, and policy makers. Thus, empirical research on this topic in the last couple of years has grown exponentially. However, there exist only a few papers dealing with herding behavior that consider the Croatian stock market. This study employs the quantile regression approach of estimating several herding investor behavior models of this market for the first time in the literature. Based upon daily data for the 37 most liquid stocks in the Zagreb Stock Exchange (ZSE) for the period September 22, 2014 to May 8, 2018, several model specifications are determined using quantile regression. Because the quantile regression approach deals with specific characteristics of financial data (stylized facts) better than the OLS method, more robust results can be achieved for evaluating if herding behavior is present in the Croatian market. The results indicate very weak to almost nonexistent evidence of herding behavior in the ZSE. Moreover, market volatility does not have any effect on herding behavior. Finally, the economic and political crisis (regarding concern Agrokor) in 2017 was controlled for in the model and the crisis was found insignificant. It seems that herding behavior does not need to be taken into account when tailoring investment strategies on the ZSE.
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