[This study uses two representative cross-sectional valuation models to examine trends in the explanatory power of given sets of financial data for security prices. The primary objective is to examine joint hypotheses on the validity of valuation models and the manner in which financial statement data are assimilated into the information set reflected in prices, and subsequently replaced by other data. The observed trends support the informativeness trend hypotheses, suggesting that the valuation models studied capture important elements of the security pricing relationship. An examination of intra-year movements showed substantial variation around the trends, suggesting the presence of temporary influences on model explanatory power. Possible explanations for these phenomena are offered.]

Abstract. One of the objectives of segment reporting, as expressed in the FASB's Statement of Financial Accounting Standards Number 14, is to enable investors to improve their assessments of companies' opportunities for future growth. Implicit in this idea are the assumptions that (1) industry membership provides information on companies' growth prospects, and (2) segment data provide incremental information over consolidated data for assessing industry‐related growth prospects. This research examines these assumptions by using an informational perspective for earnings. The informational perspective on accounting information posits that a role of accounting data such as earnings is to alter investors' beliefs about a company's future dividend paying ability, as reflected in its prospective cash flows. Specifically, this study shows that the relationship between earnings amounts and current security prices depends on whether the earnings originate from high growth or low growth industries, as defined in the paper. Furthermore, segment data appear to improve the informativeness of such an earnings classification for explaining security prices. The results suggest that investors use information on industry growth prospects in analyzing individual companies, and that segment information plays a useful role in improving such analyses. Résumé. L'un des objectifs de l'information sectorielle, tel qu'il est exprimé dans le Statement of Financial Accounting Standards No. 14 du FASB, est de permettre aux investisseurs d'évaluer avec plus de précision le potentiel de croissance des entreprises. Certaines hypothèses sont implicites à cet objectif: 1) l'appartenance au secteur donne accès à de l'information sur les perspectives de croissance des entreprises et 2) les données sectorielles offrent un supplément d'information, par rapport aux données consolidées, dans l'évaluation des perspectives de croissance liées au secteur. L'auteur examine ces hypothèses dans l'optique du contenu informationnel des bénéfices. Cette optique sur l'information comptable établit le principe selon lequel l'un des rôles de données comptables telles que les bénéfices consiste à modifier les convictions des investisseurs au sujet du potentiel de l'entreprise en termes de dividendes, tel que le reflètent ses flux monétaires éventuels. L'étude démontre précisément que la relation entre le montant des bénéfices et le cours des titres dépend du fait que les bénéfices proviennent de secteurs à forte ou à faible croissance, selon la définition du texte. De plus, les données sectorielles semblent améliorer le pouvoir explicatif de cette classification des bénéfices quant au cours des titres. Les résultats obtenus laissent supposer que les investisseurs utilisent l'information sur les perspectives de croissance du secteur dans l'analyse des différentes sociétés, et que cette information sectorielle joue un rôle appréciable dans l'amélioration de ce genre d'analyse.

Abstract ABSTRACT: This study uses two representative cross-sectional valuation models to examine trends in the explanatory power of given sets of financial data for security prices. The primary objective is to examine joint hypotheses on the validity of valuation models and the manner in which financial statement data are assimilated into the information set reflected in prices, and subsequently replaced by other data. The observed trends support the informativeness trend hypotheses, suggesting that the valuation models studied capture important elements of the security pricing relationship. An examination of intra-year movements showed substantial variation around the trends, suggesting the presence of temporary influences on model explanatory power. Possible explanations for these phenomena are offered.

We assess potential information transfers by examining the association between the earnings announcements of early and late announcers in an industry. Our earnings prediction models are statistically significant much more frequently than would be expected by chance. The models suggest potential positive information transfers on average, but there is substantial cross-industry variation in the strength of this relation. We find that the greatest price reactions by nonannouncers to same-industry earnings announcements occur in industries with the greatest earnings comovement

Robert N. Freeman, Senyo Tse, The Multiperiod Information Content of Accounting Earnings: Confirmations and Contradictions of Previous Earnings Reports, Journal of Accounting Research, Vol. 27, Current Studies on The Information Content of Accounting Earnings (1989), pp. 49-79

ABSTRACT 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.

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 accuracy is not all that matters.

Abstract Previous empirical research on the informativeness of earnings has focused on stockholders, and has not examined differences in earnings' informativeness for stockholders and bondholders. Because stockholders are residual claimants and bondholders are fixed claimants, the informativeness of earnings should differ for these two types of investors. When a firm's default risk is low, changes in its financial condition should be of limited relevance to bondholders, but should be relevant to stockholders. In contrast, as the likelihood of financial distress increases, stockholders' limited liability allows them to abandon the firm to the bondholders (Fischer and Verrecchia 1997). Accordingly, as a firm's default risk increases, changes in its financial condition should be increasingly important to bondholders and less important to shareholders. Because earnings provide information on firm value, the stock return‐earnings association should decrease as the firm's financial strength declines, while the bond return‐earnings association should increase. We use two measures of a firm's financial strength: the firm's bond rating and its reporting of a loss. Consistent with our hypotheses, we find that the association between stock returns and changes in annual earnings decreases as bond ratings decline, while the association between bond returns and changes in annual earnings increases. These results suggest that as the company's financial condition deteriorates, earnings become less relevant for stock valuation and more relevant for bond valuation. When we partition firms based on their loss status, we find a stronger association between stock returns and annual earnings changes for firms with positive earnings (profit firms) than for firms with losses, consistent with earlier studies. In contrast, we find that the association between bond returns and earnings changes is greater for loss firms than for profit firms. These results suggest that losses reduce the informativeness of earnings for stockholders but increase informativeness for bondholders, suggesting that investors view losses as indicating increased credit risk.

Abstract The Ohlson (1995) and Feltham and Ohlson (1995) valuation model provides a rigorous framework for summarizing the information in expected future earnings and book values. However, the model provides little guidance on selecting an empirical proxy for expected future earnings. We examine whether and under what circumstances historical earnings and analyst earnings forecasts offer comparable explanation of security prices. This issue is of particular interest because analyst forecasts are less readily available than historical data. Under appropriate circumstances, historical data may allow wider use of the Feltham‐Ohlson valuation model by researchers and investors. A related issue is the incremental explanatory power of historical earnings and realized future earnings (perfect‐foresight forecasts) for security prices beyond analyst forecasts. If historical earnings are incrementally informative, that would suggest that analyst forecasts do not fully reflect price‐relevant information in past earnings. If future earnings are incrementally informative, that would suggest that security prices reflect investors' implicit earnings forecasts beyond analyst forecasts. We examine these issues using a historical model (based on past earnings), a perfect‐foresight model (based on realized future earnings), and a forecast model (based on Value Line earnings forecasts). All three models provide significant explanatory power for security prices, and each set of earnings data provides incremental explanatory power for prices when used with the other sets of earnings data. We estimate the models separately for firms with moderate and extreme earnings‐to‐price (E/P) ratios, a proxy for earnings permanence. For moderate‐E/P firms, the historical model's explanatory power exceeds that of the perfect foresight model, and is indistinguishable from that of the analyst forecast model. In contrast, for extreme‐E/P firms, the perfect‐foresight model offers greater explanatory power than the historical model, but lower explanatory power than analyst forecasts. Our results suggest that financial analysts' forecasting efforts are best focused on firms whose earnings contain large temporary components (extreme E/P firms). However, in general, both historical data and analyst forecasts are complementary information sources for security valuation.