The Effect of Extreme Accounting Events on Analyst Following and Forecast Accuracy
Andrew W. Alford
Goldman, Sachs & Co.
Philip G. Berger
University of Chicago - Booth School of Business
This paper uses a simultaneous equations system to examine the effect of extreme accounting events in the previous fiscal year on analyst following and forecast accuracy. We measure extreme accounting events by the magnitude of a company's restructuring charges and by an information signal based on the fundamental variables in Lev and Thiagarajan (1993). Our results indicate that the existence of an extreme accounting event impairs analysts' ability to predict future earnings. These results are consistent with our hypothesis and suggestions in the popular press that market participants have difficulty understanding the implications of extreme accounting events for future operating performance. We also find that forecast accuracy and analyst following are determined simultaneously, with greater accuracy associated with higher analyst following. Our results suggest analysts prefer to follow companies for which earnings are easier to forecast, consistent with analysts complementing rather than substituting for other sources of information.
JEL Classification: G12, D82, M41
Date posted: July 28, 1997