https://www.mit.edu/~kothari/attach/KLW%20paper%20May%202001.pdf

Performance matched discretionary accrual measures

The conservatism principle and the asymmetric timeliness of earnings1

Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work.

/pdf/understanding-earnings-quality-a-review-of-the-proxies-their-1r9rjtuq8l.pdf

Understanding Earnings Quality: A Review of the Proxies, Their Determinants and Their Consequences

The information content of losses

This study seeks to discriminate between competing explanations of "post-earnings-announcement drift." Ball and Brown [1968] were the first to note that even after earnings are announced, estimated cumulative "abnormal" returns continue to drift up for "good news" firms and down for "bad news" firms. Foster, Olsen, and Shevlin [1984] (henceforth FOS) are among the many who have replicated the phenomenon.' FOS estimate that over the 60 trading days subsequent to an earnings announcement, a long position in stocks with unexpected earnings in the highest decile, combined with a short position in stocks in the lowest decile, yields an annualized "abnormal" return of about 25%, before transactions costs. Competing explanations for post-earnings-announcement drift fall into two categories. One class of explanations suggests that at least a portion of the price response to new information is delayed. The delay

Post-earnings-announcement drift - delayed price response or risk premium

This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness with career concerns and ability; (2) bold forecasts are more accurate than herding forecasts; and (3) herding forecast revisions are more strongly associated with analysts' earnings forecast errors (actual earnings—forecast) than are bold forecast revisions. Thus, bold forecasts incorporate analysts' private information more completely and provide more relevant information to investors than herding forecasts.

Financial Analyst Characteristics and Herding Behavior in Forecasting

This study presents evidence that the marginal response of stock price to unexpected earnings declines as the absolute magnitude of unexpected earnings increases. Most previous studies assume a linear relation between unexpected returns (UR) and unexpected earnings (UE). The constant marginal response of prices to earnings in linear models is typically referred to as the earnings response coefficient (ERC) and estimated as the slope coefficient from simple linear regression of UR on UE. Relative to the linear model, a nonlinear approach provides both significantly higher explanatory power and a richer explanation for differences between ERCs and price-earnings ratios. The nonlinear relation described in this paper rests on the premise that the absolute value of unexpected earnings is negatively correlated with earnings persistence. Valuation theory suggests that analysts and investors should place greater emphasis on forecasting high-persistence earnings than low-persistence earnings, because a given amount of the former has a greater valuation impact than the same amount of the

https://www.jstor.org/stable/pdfplus/2491123.pdf

A nonlinear model of security price responses to unexpected earnings

Prior research suggests that investors' response to analyst forecast revisions increases with the analyst's forecast accuracy. We extend this research by examining whether investors appear to extract all of the information that analyst characteristics provide about forecast accuracy. We find that only some of the analyst characteristics that are associated with future forecast accuracy are also associated with return responses to forecast revisions. This suggests that investors fail to extract some of the information that analyst characteristics can provide about future forecast accuracy. In addition, forecast properties other than expected accuracy appear to be value‐relevant. For example, investors respond more strongly to forecasts released earlier in the year and to forecasts by analysts employed by large brokerages than appears warranted by the ability of forecast timeliness and broker size to predict forecast accuracy. We conclude that investors respond to analysts' forecast revisions as if forecast...

Do Investors Respond to Analysts' Forecast Revisions as if Forecast Accuracy Is All That Matters?

In this study, we propose and test the hypothesis that investors reevaluate earnings announcements in the light of postannouncement information.1 Our argument for multiperiod price reactions to earnings news is motivated by the literature linking price responses to earnings persistence.2 When earnings are announced, we assume that investors are unable to determine with certainty the persistence of an earnings

Senyo Y. Tse

Papers

Financial Analyst Characteristics and Herding Behavior in Forecasting

A nonlinear model of security price responses to unexpected earnings

Do Investors Respond to Analysts' Forecast Revisions as if Forecast Accuracy Is All That Matters?

The Multiperiod Information Content of Accounting Earnings: Confirmations and Contradictions of Previous Earnings Reports

An earnings prediction approach to examining intercompany information transfers