Rational Bias and Herding in Analysts' Recommendations

Posted: 3 Dec 2009 Last revised: 14 Sep 2011

See all articles by Min S. Kim

Min S. Kim

Boston University; Financial Research Network (FIRN)

Fernando Zapatero

Boston University - Questrom School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: December 1, 2009

Abstract

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, G24

Suggested Citation

Kim, Min S. and Zapatero, Fernando, Rational Bias and Herding in Analysts' Recommendations (December 1, 2009). Available at SSRN: https://ssrn.com/abstract=1517571

Min S. Kim (Contact Author)

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Financial Research Network (FIRN) ( email )

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Fernando Zapatero

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

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