Rational Bias and Herding in Analysts' Recommendations
Min S. Kim
University of New South Wales; Financial Research Network (FIRN)
University of Southern California - Marshall School of Business
December 1, 2009
Using a model without conflicts of interest and with identical information available to equity analysts, we show that bias and herding in their stock recommendations occur due to incentives provided by relative performance evaluation and top awards. Furthermore, these incentives also lead to dispersion of recommendations. In particular, and contrary to commonly held views, high dispersion is more likely to arise for stocks with low volatility, for which bold recommendations increase chances of attaining top analyst status. Our empirical analysis supports this negative relationship between return volatility and recommendation dispersion, especially for large stocks, for which less information asymmetry among analysts is likely.
Keywords: stock recommendation, bias, herding, relative performance evaluation
JEL Classification: C72, G10, G24working papers series
Date posted: December 3, 2009 ; Last revised: September 14, 2011
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