This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Although analyst forecasts are generally more accurate than time-series model forecasts (e.g., O'Brien [1988]), analyst forecasts are not clearly superior to time-series model forecasts as a proxy for expected earnings (e.g., Brown et al. [1987b]). Recent research has concluded that earnings expectations reflected in stock prices at least partially reflect a seasonal random walk (SRW) model (Bernard and Thomas [1990] and Abarbanell and Bernard [1992]). In particular, Ball and Bartov [1996] find that market earnings expectations incorporate the sign of the serial correlation in seasonally differenced earnings but underestimate the correlation magnitude (see also Maines and Hand [1996]). These findings suggest that at least some market participants ignore public information in forming expected earnings; I examine whether information usage is correlated with investor sophistication and/or the degree to which investors are informed.

The accuracy of sell-side analysts' forecast revisions is related to a number of factors, including characteristics of the analyst and the age of the forecast. In this study we examine whether there are differences in how sophisticated and unsophisticated investors use these factors to predict the relative accuracy of forecast revisions. We adapt the lens model methodological approach from the judgment and decision-making literature to investigate these differences in an archival setting. Our results suggest that sophisticated investors have greater knowledge overall about the relation of the factors to forecast accuracy. Further, our evidence is consistent with sophisticated investors relying more on the specific factors that provide the most benefits (relative to their costs) for predicting relative forecast accuracy.

We examine the effects of analysts' celebrity on investor reaction to earnings forecast revisions. We measure celebrity as the quantity of media coverage analysts receive in sources included in the Dow Jones Interactive database, and find that media coverage is positively related to investor reaction to forecast revisions. The effect of celebrity on the reaction to forecast revisions remains significant after controlling for forecast performance variables examined in prior studies (ex post forecast accuracy, ex ante accuracy, award status, and other variables shown to be related to forecast accuracy). While these results are consistent with the familiarity of the analyst's name affecting the market reaction, we cannot rule out that our measure of celebrity is correlated with error in the performance measures we examine and/or correlated with other unexamined dimensions of forecast performance. A content analysis of a random subsample of the media coverage of our sample analysts suggests that our findings likely are not due to the increased availability of forecast revisions. Finally, an investigation of the excess returns around the quarterly earnings announcement date suggests that market participants react too strongly to forecast revisions issued by analysts with high levels of media coverage. Taken together, these findings suggest that an analyst's level of media coverage can affect the initial market reaction to his forecast revisions.

We examine if analysts more fully incorporate prior earnings and returns information in their current quarter forecasts as their experience following a firm increases. We measure analyst firm-specific forecasting experience as the number of prior quarters for which the analyst has issued an earnings forecast for the firm. We find that analysts underreact to prior earnings information less as their experience increases, suggesting one reason why analysts become more accurate with experience.

This paper provides evidence that managers strategically select the prior-period earnings amount that is used as a benchmark to evaluate current-period earnings in quarterly earnings announcements. Managers are more likely to separately announce a prior-period gain from the sale of property, plant, and equipment (PPE) than a loss. This strategy provides the lowest possible benchmark for evaluating current earnings, thereby allowing the manager to highlight the most favorable change in earnings. This strategic disclosure behavior is more likely to occur when it prevents a negative earnings surprise. The observed strategic disclosure decisions are consistent with a conjecture by managers that the nonrecurring nature of the prior-period gain/loss will be forgotten unless it is separately announced. Consistent with this conjecture, there is some evidence that equity investors, one potential target of strategic reporting, use the benchmark that managers provide in earnings announcements to evaluate current earnings, even when the components of this benchmark have different persistence. However, cross-sectional analyses provide no evidence that managers ex post exploit the equity mispricing that occurs between the earnings announcement date and the release of the financial statements.

Michael B. Mikhail, Beverly R. Walther, Richard H. Willis, Do Security Analysts Improve Their Performance with Experience?, Journal of Accounting Research, Vol. 35, Studies on Experts and the Application of Expertise in Accounting, Auditing, and Tax (1997), pp. 131-157

We investigate whether security analysts exhibit persistence in their stock picking ability. We find that analysts whose recommendation revisions earned the most (least) excess returns in the past continue to outperform (underperform) in the future. Further, the market recognizes these performance differences in the five-day period surrounding the recommendation revision. This market reaction, however, is incomplete. Excess returns in the one and three trading months following the revision are significant and positively associated with analysts’ prior performance. However, a trading strategy taking long (short) positions in recommendation upgrades (downgrades) conditional on analysts’ prior performance is unprofitable.