Information Content of Revised Earnings Forecasts, Market Learning, and Analyst Behavior

In my first essay, I examine how the quality of private information and the quality of public information contained in analyst revised one-year-ahead earnings forecasts issued right after a quarterly earnings announcement affect the post-earnings announcement drift (PEAD). I find that high precision of private information contained in revised forecasts reduces the level of PEAD and that the precision of public information contained in the revised one-year-ahead earnings forecasts partially offset the reduction in PEAD. Moreover, I find the effect of precision of private information on PEAD decreases after Reg FD, which required in the year 2000 that analysts could not contact the firm insiders to obtain private information. The results suggest that high-quality private information contained in revised earnings forecasts reduces information uncertainty, which helps investors estimate the true distribution of firm value. The results also suggest that investors acknowledge the impact of legal events on the quality of information from information sources. In my second essay, I empirically test the implication of Kuhnen (2015) by examining whether the impacts of firm characteristics on financial analysts\u27 following decisions change depending on the on-going economy conditions. I also examine how analysts incorporate pessimism into their expectation of distribution of firm value after observing negative events. I find that analysts become less sensitive to firm size, shares outstanding, and stock volatility when making following decisions after observing bad outcomes. However, analysts are more sensitive to prior stock performance after observing these. In addition, I find that analysts fail to fully recognize the impact of the recession on the firm\u27s performance on time, but they do incur asymmetric learning as analysts deliver forecasts with pessimistic bias after observing bad outcomes last year