| This dissertation consists of three essays in empirical asset pricing. In the first chapter, I examine the relationship between analysts' use of public information and the performance of their stock recommendations. I construct a measure of analysts' reliance on public information (RPI) based on the sensitivity of their recommendation revisions to quantitative variables that are known to predict returns. I find a strong negative relationship between analysts' past RPI and their future performance. A long/short trading strategy based on recommendation revisions of low RPI analysts yields an abnormal return of over 20% per year. My results suggest that high RPI analysts underperform not only because they have little ability to uncover private information, but also because they process the publicly available information poorly. In the second chapter, I analyze the relationship between abnormal trading volume and short-term return reversals. Unlike previous studies, I find that short-term reversals are most pronounced for high volume losers and low volume winners. Using the NYSE TAQ dataset to estimate individual investors' trades, I show that the relationship between volume and reversals can possibly be explained by attention-based trading of individual investors. Finally, in the third chapter, I examine the relationship between analysts' past earnings forecast accuracy and the performance of their future recommendations. |
