Prior research reports seemingly conflicting evidence and interpretations concerning the relation between dispersion in analysts' earnings forecasts and stock returns. Diether et al. (2002) and Johnson (2004) find 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 (L'Her and Suret 1996). 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 Johnson's (2004) explanation that dispersion levels reflect idiosyncratic uncertainty that increases the option value of the firm and generally refute Diether et al.'s (2002) explanation that dispersion levels reflect information asymmetry. In addition, we reconcile L'Her and Suret's (1996) findings with the findings of Johnson (2004). We find that the negative association between changes in dispersion and contemporaneous stock returns is not due to increased uncertainty but rather increased information asymmetry.

This study examines the association between firms’ intangible assets and properties of the information contained in analysts’ earnings forecasts. We hypothesize that analysts will supplement firms’ financial information by placing greater relative emphasis on their own private (or idiosyncratic) information when deriving their earnings forecasts for firms with significant intangible assets. Our evidence is consistent with this hypothesis. We find that the consensus in analysts’ forecasts, measured as the correlation in analysts’ forecast errors, is negatively associated with a firm’s level of intangible assets. This result is robust to controlling for analyst uncertainty about a firm’s future earnings, which we also find to be higher for firms with high levels of internally generated (and expensed) intangibles. Given that analyst uncertainty increases and analyst consensus decreases with the level of a firm’s intangible assets, we also expect and find that the degree to which the mean forecast aggregates private information and is more accurate than an individual analyst’s forecast increases with a firm’s intangible assets. Finally, additional analysis reveals that lower levels of analyst consensus are associated with high‐technology manufacturing companies, and that this association is explained by the relatively high R&D expenditures made by these firms. Overall, our results are consistent with financial analysts augmenting the financial reporting systems of firms with higher levels of intangible assets (in terms of contributing to more accurate earnings expectations), particularly R&D‐driven high‐tech manufacturers.

This paper presents a model that relates properties of the analysts' information environment of the properties of their forecasts. First, we express forecast dispersion and error in the mean forecast in terms of analyst uncertainty and consensus (that is, the degree to which analysts share a common belief). Second, were reserve the relations to show how uncertainability and consensus cab be measured by combining forecast dispersion, error in the mean forecast, and the number of forecasts. Third, we show that the quality of common and private information available to analysts can be measured using these same observable variables. The relations we present are intuitive and easily applied in empirical studies.