Performance, Herding, and Career Concerns of Individual Financial Analysts

Abstract:     
Using a new database of stock recommendations with substantially expanded coverage of brokerage firms and individual analysts, I examine the performance of portfolios recommended by individual analysts. The analysis allows a more accurate measurement of analyst performance with extensive risk adjustments. I show that at the aggregate level, analyst portfolios generate significant abnormal returns. Individually, a large number of analysts significantly outperform risk-adjusted benchmarks and there are at least twice as many analysts who significantly outperform as analysts who significantly underperform benchmarks. Abnormal performance is generated mainly within a narrow event window from two trading days before the recommendation date to five trading days later, with no significant post-event return drift. In addition, analyst performance improves with the number of recommendations issued, the number of stocks covered, and the size of their brokerage firms. However, performance declines as their coverage goes beyond 12-13 stocks. All-American analyst ranking of Institutional Investor cannot predict analyst performance. Moreover, analysts career concerns have significant impact on their behavior. Analysts with more reputation capital at stake recommend less risky portfolios and deviate less from the herd. Analyst behavior is also predictable on the basis of several other characteristics. Furthermore, I provide evidence for the current debate on how to reform analyst compensation. I find although the II all-star ranking is significantly related to performance, it is affected more by recognition factors and reputation factors. Its capacity to serve as a performance-based evaluation system for analyst compensation is quite limited.

Keywords: market efficiency, analyst characteristics, analyst compensatin, analyst behavior

JEL Classifications: G11, G14, G18, J30

Working Paper Series