In this paper, we propose and empirically test a cross‐sectional profitability forecasting model which incorporates two major improvements relative to extant models. First, in terms of model construction, we incorporate mean reversion through the use of a two‐stage partial adjustment model and inclusion of a number of additional relevant determinants of profitability. Second, in terms of model estimation, we employ least absolute deviation (LAD) analysis instead of ordinary least squares because the former approach is able to better accommodate outliers. Results reveal that forecasts from our model are more accurate than three extant models at every forecast horizon considered and more accurate than consensus analyst forecasts at forecast horizons of two through five years. Further analysis reveals that LAD estimation provides the greatest incremental accuracy improvement followed by the inclusion of income subcomponents as predictor variables, and implementation of the two‐stage partial adjustment model. In terms of economic relevance, we find that forecasts from our model are informative about future returns, incremental to forecasts from other models, analysts’ forecasts, and standard risk factors. Overall, our results are important because they document the increased accuracy and economic relevance of a cross‐sectional profitability forecasting model which incorporates improvements to extant models in terms of model construction and estimation.

Some firms voluntarily make disclosures about the controls and processes in place to ensure the reliability of fair value estimates. Consistent with these disclosures being driven by investors’ concerns about the reliability of their SFAS 157 estimates, we find that firms with more opaque estimates are more likely to provide such disclosures. We then examine whether these disclosures improve investors’ perception about the reliability of fair value estimates. We find that they are associated with higher market pricing and lower information risk for Level 3 estimates. Further analyses of the disclosures reveal that the following types of information are particularly important to investors: discussion of the external and independent pricing of fair value estimates and their proper classification according to the SFAS 157 hierarchy. Overall, our results suggest that the voluntary reliability disclosures that firms provide beyond SFAS 157’s three-level estimates help reduce investors’ uncertainty toward the more opaque fair value estimates.