In this study I investigate the relation between information complexity and financial analysts' use of that information. I rank by complexity six tax-law changes enacted by the Tax Reform Act of 1986, and then examine analysts' explicit forecasts of effective tax rates around those changes. I show that analysts' revisions of their forecasts of effective tax rates appear to impound the effects of the less complex tax-law changes but not the more complex changes. Furthermore, as expected, if analysts assimilate less complex (but not more complex) information, the magnitude of the errors in their forecasts of effective tax rates increases with the effects of the more complex tax-law changes, but is unrelated to the less complex changes. Taken together, these results indicate that analysts assimilate less complex information to a greater extent than they assimilate more complex information. Either analysts' abilities to incorporate specific information into their forecasts is a decreasing function of the complexity of that information, or analysts choose not to assimilate complex information because the cost would exceed the benefit. In either case, complexity reduces analysts' use of information. These results demonstrate the importance of considering information attributes, such as complexity, when investigating why analysts' forecasts fail to incorporate all public information.

Management earnings forecasts expressed as a range have become the most common form of quantitative management guidance. Traditionally, the proxy for the sign and the magnitude of the information conveyed by these forecasts—the forecast news—is calculated as the difference between a pre‐forecast earnings expectation and the midpoint of the forecasted range. We provide strong evidence that this traditional measure understates the amount of information conveyed by range forecasts. More importantly, we demonstrate that information conveyed by the upper and lower bounds of the forecasts can be used to improve the classification of forecasts as conveying good or bad news and for calculating the magnitude of that news. We rely on these findings to suggest alternative methods of classifying management range forecasts as conveying good versus bad news and to refine the calculation of forecast news to include the broader information set. Our analysis also suggests that the information conveyed by the range when the forecasts are bundled (issued concurrent with an earnings announcement) is significantly different than when forecasts are not bundled. Overall, our study documents the importance of incorporating range‐related information when assessing the sign and the magnitude of the information conveyed by management range forecasts.

Managers, investors, and researchers have a compelling interest in identifying a reliable empirical proxy for firm-specific cost of equity capital (r). In theory, deducing r is possible if the market's future cash flow forecast and current stock price are observable. Practically, deducing r is dependent on the ability to estimate the market's forecasted terminal value. We evaluate five methods of deducing firm-specific r (labeled rDIVPREM, rGLSPREM, rGORPREM, rOJNPREM, and rPEGPREM) that deal with this conundrum differently. The extent to which the estimates are associated with firm risk in a stable and meaningful manner is the basis for our assessment. We find that the rDIVPREM and rPEGPREM estimates are consistently and predictably related to risk, while the alternatives are not. Based on these results, we conclude that rDIVPREM and rPEGPREM dominate the alternatives.

Theoretical work generally predicts a negative association between disclosure and risk premium, where additional disclosure reduces estimation risk or information asymmetry. However, empirical studies frequently report mixed results. Recent theoretical studies suggest that the association between disclosure and risk premium is not necessarily always negative, and could be positive (or less negative). For example, Dutta and Nezlobin (2017) show that disclosure can be associated with higher risk premium when conditioned on a firm's growth rates. Similarly, Johnstone (2016) shows that higher signal quality can lead to higher risk premium. Motivated by these studies, we re-examine the association between disclosure and risk premium, conditional on growth. Using various proxies for risk premium, disclosure, and growth, we provide robust evidence that while the unconditional association between disclosure and risk premium is ambiguous, the conditional association is negative for lower growth firms but is less negative (or positive) for higher growth firms. Data Availability: Additional analyses are available from the authors upon request.