Analyst information precision and small earnings surprises

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings

A Better Measure of Institutional Informed Trading

Although many studies show that the presence of institutional investors facilitates the incorporation of accounting information into financial markets, the evidence of informed trading by institutions is rather limited in the extant literature. We address these inconsistent findings by proposing PC_NII, percentage changes in the number of a stock's institutional investors, as a novel informed trading measure. PC_NII is better able to detect informed trading than are changes in institutional ownership (?IO)—the measure commonly used in previous studies—because (i) entries and exits are usually triggered by substantive private information and (ii) only a small fraction of institutions have superior information. As conjectured, PC_NII subsumes the information content of ?IO and other institutional trading and herding measures in the forecast of stock returns, and its strong predictive power for stock returns reflects mainly its close correlation with future earnings surprises. We also show that PC_NII helps address empirical issues that require a reliable measure of institutional informed trading