声誉
关系(数据库)
业务
星星
心理学
精算学
互联网隐私
计算机科学
政治学
天体物理学
法学
数据挖掘
物理
作者
Lily H. Fang,Ayako Yasuda
出处
期刊:Social Science Research Network
[Social Science Electronic Publishing]
日期:2010-01-01
被引量:36
摘要
Using 1994-2009 data, we examine the relation between analysts’ star status and their recommendation values. For investors with private, advance access to analyst recommendations (e.g., institutions), trading on All-American (AA) analysts’ buy and sell recommendations yields significantly better risk-adjusted returns than trading on non-AAs’ recommendations. For investors without such access (e.g., individuals), only top-rank AAs make significantly more profitable buy recommendations than others. AAs outperform non-AAs both before and after they are elected, and the performance differential does not reverse. Reg-FD, Rule 2711, and the Global Settlement did not significantly erode the performance differential between AAs and non-AAs. Furthermore, election to top-AA ranks predicts performance in buy recommendations even among analysts with high ex-ante election probabilities. Collectively, these results suggest that skill differences among analysts exist and AA election reflects institutional investors’ ability to evaluate and benefit from elected analysts’ superior skills. Public investors’ opportunity to profit from the stars’ opinions exists, but is limited due to their timing disadvantage.
科研通智能强力驱动
Strongly Powered by AbleSci AI