This paper provides a theoretical explanation and consistent empirical evidence for the increase in the contemporaneous correlation between returns and aggregate earnings as the return interval is lengthened. Consistent with intuition and with Easton, Harris, and Ohlson 1992, the analysis shows that aggregation over time renders the lag in accounting recognition relatively less important and thus improves the returns‐earnings R 2 . Interestingly, the analysis also reveals that aggregating earnings over longer periods increases the positive covariance between aggregate earnings and the accounting lag, which may further increase the R 2 . This positive covariance can lead to an earnings coefficient greater than one over some range of aggregation, which is consistent with the findings of Easton et al. that over the 10‐year interval the returns‐earnings regression slope coefficient is greater than one (1.7). The empirical results highlight the fact that the slope coefficient, which is greater than one and increasing with the interval, accounts for much of the increment to the returns‐earnings R 2 . In fact, constraining the slope coefficient to be one results in an R 2 of 11 percent for the 10‐year interval, which is considerably lower than the R 2 of 47 percent when the regression is unconstrained. Hence, the positive covariance between current earnings and the accounting lag, rather than the diminishing effect of the accounting lag, appears to be the dominant explanation for the observed high R 2 over long intervals.

This paper provides a theoretical explanation and consistent empirical evidence for the increase in the contemporaneous correlation between returns and aggregate earnings as the return interval is lengthened. Consistent with intuition and with Easton, Harris, and Ohlson 1992, the analysis shows that aggregation over time renders the lag in accounting recognition relatively less important and thus improves the returns-earnings R2. Interestingly, the analysis also reveals that aggregating earnings over longer periods increases the positive covariance between aggregate earnings and the accounting lag, which may further increase the R2. This positive covariance can lead to an earnings coefficient greater than one over some range of aggregation, which is consistent with the findings of Easton et al. that over the 10-year interval the returns-earnings regression slope coefficient is greater than one (1.7). The empirical results highlight the fact that the slope coefficient, which is greater than one and increasing with the interval, accounts for much of the increment to the returns-earnings R2. In fact, constraining the slope coefficient to be one results in an R2 of 11 percent for the 10-year interval, which is considerably lower than the R2 of 47 percent when the regression is unconstrained. Hence, the positive covariance between current earnings and the accounting lag, rather than the diminishing effect of the accounting lag, appears to be the dominant explanation for the observed high R2 over long intervals.

The weak correlation between accounting earnings and security returns documented by numerous empirical studies is an issue of concern in current accounting research. Given that price is determined not solely by accounting earnings but also by other sources of information about future earnings, this paper focuses on the relation between earnings and other information to understand the returns‐earnings association. The analysis indicates that current earnings exhibit high explanatory power for returns if they correlate with expected future earnings (or with other information that reflects expected future earnings). A high price‐to‐earnings (P/E) ratio coupled with a high return on equity (ROE) can ex ante indicate earnings growth, and the earnings of firms with these attributes are positively correlated with future earnings. The high‐growth subset obtains an impressive returns‐earnings R 2 of 31 percent and an earnings coefficient of 6.17, demonstrating that it is possible to identify firms whose earnings are strongly correlated with returns using a parsimonious set of firm characteristics. Résumé. La faible corrélation entre les bénéfices comptables et le rendement des titres de placement sur laquelle se sont penchés de nombreux auteurs d'études empiriques retient aujourd'hui l'attention des chercheurs en comptabilité. Le cours des titres étant déterminé non seulement par les bénéfices comptables mais aussi par d'autres sources d'information relative aux bénéfices futurs, l'auteur s'intéresse ici à la relation entre les bénéfices et d'autres renseignements, dans le but d'expliquer le lien entre rendement et bénéfices. L'analyse révèle que les bénéfices courants ont un pouvoir explicatif élevé à l'égard du rendement si ce dernier est en corrélation avec les bénéfices futurs prévus (ou avec d'autres renseignements indicateurs des bénéfices futurs prévus). Un ratio cours/bénéfice élevé associé à un rendement des capitaux propres élevé peut indiquer, ex ante , une croissance des bénéfices, et les bénéfices des entreprises qui possèdent ces caractéristiques sont en corrélation positive avec les bénéfices futurs. Le sous‐groupe des entreprises à forte croissance obtient un R 2 étonnant de 31 pour cent, résultat d'une analyse de régression du rendement par rapport aux bénéfices, et un coefficient de bénéfices de 6,17, ce qui démontre qu'il est possible de déterminer quelles sont les entreprises dont les bénéfices présentent une forte corrélation avec le rendement, lorsqu'on utilise un ensemble parcimonieux de caractéristiques des entreprises.

This is an accepted manuscript of an article published by Wiley in Contemporary Accounting Research.

We test the asymmetric timeliness hypothesis by using information in extreme events as a measure of good/bad news. Our focus on extreme events is motivated by two arguments. First, the accounting concept of materiality in conjunction with litigation risk influences managers and auditors to make more conservative choices with respect to material events. Second, focusing on extreme shocks minimizes the probability that accounting slack may obscure the effect of asymmetric timeliness (Beaver and Ryan 2005). We identify individual events using short‐window extreme returns, since long‐window returns would aggregate the effect of multiple events and thus limit our ability to detect the asymmetry. Taken together, these features of our research design provide a more powerful test of asymmetric timeliness. Consistent with prior studies, we document that the correlation between bad news and concurrent earnings is significantly higher than that between good news and concurrent earnings. Our analysis of extreme events also enables us to document higher correlation of good news with earnings two or more quarters ahead. This is in contrast to prior studies that were unable to document asymmetry in the relation between returns and subsequent earnings in the opposite direction to that between returns and concurrent earnings. Our paper contributes to the growing literature on conservatism by modifying the Basu methodology to enhance the power of the test of asymmetric timeliness.

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross‐sectional analysis suggests that more sophisticated analysts and superior long‐term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts' earnings forecasts are negatively associated with the degree of conservatism; that is, analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings‐based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.