Analyst information production and the timing of annual earnings forecasts

We investigate whether the reputation-herding theory or the tradeoff theory explains variation in the timing of individual analysts’ forecasts. Using forecast accuracy improvements, forecast boldness, and the price impact of forecasts as measures of forecast quality, we find that in the information discovery phase that precedes an earnings announcement, earlier forecasts have higher quality than later forecasts. We also find a similar pattern in the information analysis phase that begins with the earnings announcement date. Our findings suggest that consistent with the herding theory, analysts who are more capable participate early in discovering and analyzing information, and therefore earlier forecasts in the information discovery and analysis phases are of higher quality than later forecasts in that phase.     

Earnings Announcements,Differences of Opinion and Management Guidance

Berkman, Dimitrov, Jain, Koch, and Tice (2009) document a negative relationship between differences of opinion and earnings announcement returns, and this relationship is more pronounced when short‐sale constraints are likely to be high. These findings are interpreted as support for the theory in Miller (1977) that binding short sale constraints cause pessimists to be underrepresented in price formation. We conjecture that accounting information (i.e., earnings news) is likely to play a role in this returns pattern. After controlling for the level of earnings news, we find that the relationship between differences of opinion and stock returns is either eliminated or opposite from what is predicted by Miller's theory. Further, we present evidence that suggests the confounding effect of earnings news can be explained by (pessimistic) management earnings guidance. Our findings offer an alternative explanation for why low differences of opinion stocks earn greater abnormal returns around earnings announcements.     

Insider trading around auto recalls: Does investor attention matter?

Review of Quantitative Finance and Accounting - Using a comprehensive sample of customer complaints filed with the National Highway Traffic Safety Administration, we examine the...     

Investors' Misweighting of Firm-Level Information and the Market's Expectations of Earnings

Prior studies use fundamental earnings forecasts to proxy for the market's expectations of earnings because analyst forecasts are biased and are available for only a subset of firms. We find that as a proxy for market expectations, fundamental forecasts contain systematic measurement errors analogous to those in analysts' biased forecasts. Therefore, these forecasts are not representative of investors' beliefs. The systematic measurement errors from using fundamental forecasts to proxy for market expectations occur because investors misweight the information in many firm-level variables when estimating future earnings, but fundamental forecasts are formed using the historically efficient weights on firm-level variables. Thus, we develop an alternative ex ante proxy for the market's expectations of future earnings (“the implied market forecast”) using the historical (and inefficient) weights, as reflected in stock returns, that the market places on firm-level variables. A trading strategy based on the implied market forecast error, which is measured as the difference between the implied market forecast and the fundamental forecast, generates excess returns of approximately 9 percent per year. These returns cannot be explained by investors' reliance on analysts' biased forecasts. Overall, our results reveal that market expectations differ from both fundamental forecasts and analysts' forecasts.     

The Effects of Disclosure and Analyst Regulations on the Relevance of Analyst Characteristics for Explaining Analyst Forecast Accuracy

We posit and find an effect of disclosure and analyst reporting regulations implemented from 2000 through 2003 (including Regulation Fair Disclosure, the Sarbanes‐Oxley Act and the Global Settlement Act) on the importance of analyst and forecast characteristics for analyst forecast accuracy. Following the enactment of these regulations, more experienced analysts and All‐Star analysts do not maintain their superior forecast accuracy, and analysts employed by large brokerage houses perform worse than other analysts. In addition, we find a decrease in the importance of analyst effort, the number of industries and firms followed, days elapsed since the last forecast, and forecast horizon. While the importance of bold upward forecast revisions does not change, bold downward revisions lose their relevance for forecast accuracy after 2003. Finally, we find an increase in the importance of prior forecast accuracy. We find that the importance of these characteristics varies with the precision of publicly available information. Specifically, the decrease in the importance of most analyst and forecast characteristics and the increase in the importance of prior forecast accuracy are greater when the precision of publicly available information is low. Overall, our results suggest that the positive effects of experience, effort, brokerage house size and All‐Star status on forecast accuracy in the pre‐regulation period were because of the information advantages that these analysts enjoyed (rather than their ability to generate private information). In contrast, our results suggest that prior forecast accuracy is related to analysts’ ability to generate private information.     

Trading concentration and industry-specific information: an analysis of auto complaints

Review of Quantitative Finance and Accounting - We investigate whether sophisticated investors’ trading concentration in the auto industry is associated with their use of auto complaint data....