May 16, 2002 | Narasimhan Jegadeesh, Joonghyuk Kim, Susan D. Krische, Charles M. C. Lee
This paper examines the value of analyst stock recommendations and their changes in predicting future stock returns. The authors find that analysts from sell-side firms generally recommend "glamour" stocks, which are characterized by positive momentum, high growth, high trading volume, and relatively high valuations. However, these recommendations can be costly because the level of consensus recommendations only adds value for stocks with favorable quantitative characteristics (high value and positive momentum). For stocks with unfavorable characteristics, higher consensus recommendations are associated with worse subsequent returns. In contrast, the quarterly change in the consensus recommendation is a robust return predictor, containing information orthogonal to other predictive variables. The study also reveals that analysts do not fully account for the predictive power of various stock characteristics and that their recommendations are influenced by economic incentives, leading to a bias towards growth stocks. The findings suggest that recommendation changes may bring new information to the market or create price momentum through the analysts' influence as opinion leaders. The research contributes to understanding how analysts evaluate stocks and their role in price formation, providing insights for both academic researchers and practitioners.This paper examines the value of analyst stock recommendations and their changes in predicting future stock returns. The authors find that analysts from sell-side firms generally recommend "glamour" stocks, which are characterized by positive momentum, high growth, high trading volume, and relatively high valuations. However, these recommendations can be costly because the level of consensus recommendations only adds value for stocks with favorable quantitative characteristics (high value and positive momentum). For stocks with unfavorable characteristics, higher consensus recommendations are associated with worse subsequent returns. In contrast, the quarterly change in the consensus recommendation is a robust return predictor, containing information orthogonal to other predictive variables. The study also reveals that analysts do not fully account for the predictive power of various stock characteristics and that their recommendations are influenced by economic incentives, leading to a bias towards growth stocks. The findings suggest that recommendation changes may bring new information to the market or create price momentum through the analysts' influence as opinion leaders. The research contributes to understanding how analysts evaluate stocks and their role in price formation, providing insights for both academic researchers and practitioners.