Researchers in accounting have recently provided evidence of a striking increase in the usefulness of earnings announcements based on stock market price and volume reactions (Beaver et al., 2018; Barron et al., 2018). Price reactions, however, are unable to capture investor disagreement and volume reactions capture both the resolution of prior disagreement and newfound disagreement generated by earnings announcements. Thus, it remains to be determined if earnings announcements have become increasingly useful in leveling the informational playing field, a key public policy objective of financial reporting. To address this possibility, we examine changes in disagreement around annual earnings announcements over the last forty years using analyst forecast measures found in the literature. First, we show that forecast dispersion is reduced around earnings announcements and this reduction has increased over time. Next, we use a forecast measure of informedness from Barron et al. (1998) to show that analysts as a group are more informed by earnings announcements in recent time periods. Finally, we use Barron et al.’s forecast measure of consensus to show that the ability of earnings announcements to make analysts more commonly informed has increased over time.

In this study, we study information processing by financial professionals benchmarked with non-professionals and how correlation among individual forecasts explains the group level forecast performance. In an experiment in which participants make price forecasts based on common financial information, we find that individual professionals are no better than individual non-professionals in forecasting, but professionals’ mean forecasts are superior. Our analysis suggests that financial professionals’ individual errors are less correlated as they process information from more diverse perspectives. This leads to superior mean forecasts because the uncorrelated individual errors cancel each other out in the aggregate. In contrast, non-professionals are similar in using salient information such as earnings or cash flow. As a result, their individual errors are highly correlated. Instead of cancelling each other out, the individual errors are enlarged in the aggregated mean forecasts. We are the first to show the difference in the comparisons of professionals and non-professionals at the group level versus at the individual level. Our paper contributes to the literature by documenting the evidence of diversity in information processing by financial professionals.

Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning, pp. 101-149 (2020) Free AccessChapter 2: Do Managers Use Earnings Forecasts to Fill a Demand They Perceive from Analysts?Orie Barron, Jian Cao, Xuguang Sheng, Maya Thevenot and Baohua XinOrie BarronPenn State University, USA, Jian CaoFlorida Atlantic University, USA, Xuguang ShengAmerican University, USA, Maya ThevenotFlorida Atlantic University, USA and Baohua XinUniversity of Toronto, Canadahttps://doi.org/10.1142/9789811202391_0002Cited by:0 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: This paper examines how the nature of the information possessed by individual analysts influences managers' decisions to issue forecasts and the consequences of those decisions. Our analytical model yields the prediction that managers prefer to issue guidance when they perceive their private information to be more precise, and analysts possess mostly common, imprecise information (i.e., there is high commonality and uncertainty). Based on an econometric model, we obtain theory-based analyst variables and our empirical evidence confirms our predictions. High commonality and uncertainty in analysts' prior information are accompanied by increases in analysts' forecast revisions and trading volume following guidance, consistent with greater analyst incentives to generate idiosyncratic information. Yet, management guidance increases only with the commonality contained in analysts' pre-disclosure information, but not with the level of uncertainty. Indeed, the disclosure propensity among a subset of firms (those with less able managers, bad news, and infrequent forecasts) has an inverse relationship with analyst uncertainty due to its reflection on the low precision of management information. Our results are robust to a variety of alternative analyses, including the use of propensity-score matched pairs with similar disclosure environments but differing degrees of commonality and uncertainty among analysts. We also demonstrate that the use of forecast dispersion as an empirical proxy for analysts' prior information may lead to erroneous inferences. Overall, we define and support improved measures of analyst information environment based on an econometric model and find that the commonality of information among analysts acts as a reliable forecast antecedent by informing managers about the amount of idiosyncratic information in the market. Keywords: Management earnings forecastsAnalysts' informationUncertaintyCommonality FiguresReferencesRelatedDetails Handbook of Financial Econometrics, Mathematics, Statistics, and Machine LearningMetrics Downloaded 222 times History KeywordsManagement earnings forecastsAnalysts' informationUncertaintyCommonalityPDF download

This study examines how financial disclosures with earnings announcements affect sell-side analysts' information about future earnings, focusing on disclosures of financial statements and management earnings forecasts. We find that disclosures of balance sheets and segment data are associated with an increase in the degree to which analysts' forecasts of upcoming quarterly earnings are based on private information. Further analyses show that balance sheet disclosures are associated with an increase in the precision of both analysts' common and private information, segment disclosures are associated with an increase in analysts' private information, and management earnings forecast disclosures are associated with an increase in analysts' common information. These results are consistent with analysts processing balance sheet and segment disclosures into new private information regarding near-term earnings. Additional analysis of conference calls shows that balance sheet, segment, and management earnings forecast disclosures are all associated with more discussion related to these items in the questions-and-answers section of conference calls, consistent with analysts playing an information interpretation role with respect to these disclosures.

This study examines how financial disclosures made with earnings announcements affect analysts’ information about future earnings, focusing on disclosures of financial statements and management earnings forecasts. We find that disclosures of balance sheets and segment data are associated with an increase in the degree to which analysts' forecasts of upcoming quarterly earnings are based on private information. Further analyses show that balance sheet disclosures are associated with an increase in the precision of both analysts' common and private information, segment disclosures are associated with an increase in analysts' private information, and management earnings forecast disclosures are associated with an increase in analysts’ common information. These results are consistent with analysts processing balance sheet and segment disclosures into new private information regarding near-term earnings. Additional analysis of conference calls shows that balance sheet, segment, and management earnings forecast disclosures are all associated with more discussion related to these items in the questions-and-answers section of conference calls, consistent with analysts playing an information interpretation role with respect to these disclosures.

This study examines the effect of the adoption of Statement of Financial Accounting Standards No. 157 Fair Value Measurements (hereafter FAS 157) on analysts’ information environment. A major controversy surrounding FAS 157 disclosures is whether Level 3 measurements provide useful information to financial statement readers. We provide evidence suggesting that FAS 157 disclosures regarding Level 3 measurements are able to reduce uncertainty in analysts’ information environment. Our results reveal that the provision of such fair value disclosures is associated with reduced uncertainty regarding future earnings and lower forecast errors. We also find that unrealized gains and losses from fair value changes in Level 3 measurements are positively associated with firms’ future performance. Overall, our findings suggest that disclosures related to FAS 157 fair value measurements improve analysts’ information environment. Our findings thus contribute to the debate regarding the extent of fair value accounting in financial reporting.

The increase in investor diversity over the last 35-40 years (ICI 2014) prompted us to revisit trading volume reactions to earnings announcements and how these reactions vary with firm size. This increase in investor diversity would likely lead to an increase in differences in the precision of pre-announcement information and potentially increase the importance of earnings announcements to resolve investor disagreement. We find that the nature of trading volume reactions to earnings announcements has fundamentally changed over the 35-year time period 1977-2011. There has been a dramatic increase in the magnitude and frequency of volume reactions to earnings announcements over this time period, and this effect is more pronounced in large firms where volume reactions were previously infrequent. The increase in large firms’ trading volume reactions is so pronounced that the relation between volume reactions and firm size has turned positive in recent years, thereby reversing Bamber’s (1986, 1987) previously documented negative relation. We provide intuition and empirical evidence that our results are attributable to the resolution of differential prior precision among an increasingly diverse set of investors following large firms.

ABSTRACT: This paper examines the ex ante effects of public information quality on market prices and how such effects vary with information asymmetry among traders in a two-period experimental market. We vary public information quality by changing its precision and information asymmetry among traders by varying the distribution of private signals. We find high-quality public disclosure leads to increased price efficiency and decreased cost of capital in the pre-announcement period when information asymmetry is high. The impending high-quality public information increases the competition among informed traders, which leads prices to impound more private information and alleviates the adverse selection problems facing uninformed traders. Our study suggests building a high-quality public information environment (e.g., by adopting high-quality accounting standards or committing to transparent disclosure policies) would likely provide ex ante benefits for firms with significant adverse selection among traders.

In this study, we show that on average relatively pessimistic analysts tend to reveal their earnings forecasts later than other analysts. Further, we find this forecast timing effect explains a substantial proportion of the well-known decrease in consensus analyst forecast optimism over the forecast period prior to earnings announcements, which helps explain why analysts' longer term earnings forecasts are more optimistically biased than their shorter term forecasts. We extend the theory of analyst self-selection regarding their coverage decisions to argue that analysts with a relatively pessimistic view-compared to other analysts-are more reluctant to issue their earnings forecasts, with the result that they tend to defer revealing their earnings forecasts until later in the forecasting period than other analysts.

In empirical tests guided by recent theory (e.g., Hughes, Liu and Liu 2007; and Lambert, Leuz and Verrecchia 2011), we examine the joint effects of information precision, information asymmetry and the level of market competition on firms’ cost of equity capital. Consistent with theory, we find that average information precision and the level of market competition reduce the positive effect of information asymmetry but do not eliminate it. Besides examining various aspects of the environment jointly, our study is also unique in that we follow the suggestions of Sheng and Thevenot (2012) for modifying the Barron, Kim, Lim and Stevens (1998) measures of information asymmetry and precision. We find that cost of equity capital varies greatly with the modified measures of information asymmetry and average information precision. For example, our regression estimates suggest that information asymmetry and average information precision are more important than equity beta and firm size in determining firms’ cost of capital, and that such a substantial effect from information asymmetry and information precision is not apparent using unmodified BKLS measures.

We argue that technological advances, changes in financial regulation, and changes in investor composition over the past 30 years have increased the available financial information of small firms and the investor diversity of large firms. This leads us to hypothesize and test for a positive shift in the relation between trading volume reactions to earnings announcements and firm size. Consistent with our hypothesis, we document a positive shift in the trading volume reaction/firm size relation between the time of Bamber’s (1986, 1987) seminal research (1977-1980) and a modern time period (2003-2006). Surprisingly, this positive shift has caused the trading volume reaction/firm size relation to turn positive, thereby reversing Bamber’s previously documented negative relation. We also provide evidence that this positive shift is driven by relative increases in differential precision of pre-announcement information in large firms.

This paper reviews, synthesizes, and critiques the capital market literature examining trading volume around earnings announcements and other financial reports. Our purposes are to assess what we have learned from examining trading volume around these announcements and to suggest directions for future research. We conclude that researchers have yet to realize the potential Beaver (1968) identified for trading volume to yield unique insights regarding the nature of earnings announcements and other financial reports, and the effects of these announcements on market participants. This state of the literature is attributable to a dearth of volume theory early on, and more recently to a disconnect between theoretical development and empirical research. Thus, we begin by briefly summarizing developments in trading volume theory since Beaver (1968). We also discuss unique measurement challenges in trading volume research, including identifying appropriate proxies for abnormal trading volume and for individual investors’ beliefs. In light of theory and empirical measurement issues, we interpret the current literature and identify directions for future research. We conclude that extant research just scratches the surface of what trading volume can reveal about the characteristics of financial disclosures and the effects of these disclosures on investors.

This study examines how the disclosure of certain financial statements (i.e., balance sheet, cash flow statement, and segment disclosure) in quarterly earnings announcements affects analysts' information about upcoming earnings. Our first test examines whether the disclosure of a financial statement prompts analysts to ask management more or fewer questions about this financial statement in the concurrent earnings conference call. Our second test examines whether the disclosure of financial statements increases or decreases analysts' private information. Both tests yield consistent evidence supporting a complementary relation between balance sheet and segment disclosures and analysts' private information.

Prior research reports seemingly conflicting evidence and interpretations concerning the relation between dispersion in analysts' earnings forecasts and stock returns. Previous studies have shown a negative relation between levels of dispersion in analysts' forecasts and future stock returns. Yet, changes in forecast dispersion are negatively associated with contemporaneous stock returns.We demonstrate that levels and changes in dispersion reflect different theoretical constructs. Changes in dispersion primarily reflect changes in information asymmetry, whereas levels of dispersion primarily reflect levels of uncertainty. Further, the uncertainty component of dispersion levels reflects idiosyncratic risk that is negatively associated with future stock returns. These findings provide support for the theory that dispersion levels reflect idiosyncratic uncertainty that increases the option value of the firm and generally refute the explanation that dispersion levels reflect information asymmetry.In addition, we reconcile the conflicting findings outlined above. We find that the negative association between changes in dispersion and contemporaneous stock returns is not due to increased uncertainty but rather to increased information asymmetry.

This study examines whether dispersion in analysts' earnings forecasts reflects uncertainty about firms' future economic performance. Prior research examining this issue has been inconclusive. These studies have concluded that forecast dispersion is likely to reflect factors other than uncertainty about future cash flows, such as uncertainty about the price irrelevant component of firms' financial reports (Daley et al. [1988]; Imhoff and Lobo [1992]). Abarbanell et al. (1995) argue that, if forecast dispersion after (i.e., conditional on) an earnings announcement reflects uncertainty about firms' future cash flows and this uncertainty causes investors to desire additional information, then dispersion will be positively associated with both (a) the level of demand for more information and (b) the magnitude of price reactions around the subsequent earnings release. In this study, we construct a measure of informational demand using the incidence of analyst forecast updating after dispersion is measured. We find a positive association between dispersion in earnings forecasts after an earnings release and this measure of informational demand. We also find a positive association between forecast dispersion and the magnitude of price reactions around subsequent earnings releases. These associations are most apparent when potentially stale (or outdated) forecasts are removed from measures of forecast dispersion. These associations also persist after controlling for other measures of uncertainty (e.g., beta and the variance of daily stock returns), consistent with dispersion in analysts' earnings forecasts serving as a useful indicator of uncertainty about the price relevant component of firms' future earnings.

Large earnings surprises and negative earnings surprises represent more egregious errors in analysts' earnings forecasts. We find evidence consistent with our expectation that egregious forecast errors motivate analysts to work harder to develop or acquire relatively more private information in an effort to avoid future forecasting failures. Specifically, we find that after large or negative earnings surprises there is a greater reduction in the error in individual analysts' forecasts of future earnings, and these individual forecasts are based more heavily on individual analysts' private information. This increased reliance on private information reduces the error in the mean forecast of upcoming earnings (even after controlling for the effect of reduced error in individual forecasts). As reliance on private information increases, more of each individual forecast error is idiosyncratic, and thus averaged out in the computation of the mean forecast.

This study examines the relation between supplemental voluntary disclosures in firms' earnings announcements and the market reactions to these announcements. We find that abnormally high trading volume around earnings announcements is associated with disclosure of balance sheets, segment reports, range forecasts, and length of conference calls. We show that these trading volume findings can be explained by the relation between voluntary disclosures and disagreement measures developed by Kandel and Pearson (1995), Barron (1995), and Barron, Kim, Lim, and Stevens (1998) - disagreement measures already shown both theoretically and empirically to explain trading volume around earnings announcements (see Holthausen and Verrecchia 1990; Kandel and Pearson 1995; Kim and Verrecchia 1997; Bamber, Barron, and Stober 1997 and 1999; Barron, Harris, and Stanford 2005). In contrast to this trading volume evidence, we find that only balance sheet disclosures have a statistically significant positive association with the magnitude of price reactions. This increases understanding of why Cready and Hurrt (2002) observe trading volume reactions around earnings announcements more often than price reactions, because several types of concurrent voluntary disclosures spur abnormal trading that does not coincide with significant price reactions.