Abstract: I show that dispersion among equity analysts' forecasts increases following earnings announcements. I provide evidence that this is due to information selection: analysts rely on different subsets of public information revealed in earnings announcements when revising their forecasts in a high-dimensional setting. Using text data from analysts' reports, I show that analysts cite different information when they revise their forecasts following earnings announcements, providing evidence of information selection. Results from elastic net regressions corroborate these findings but further imply the existence of a common benchmark to which analysts can compare their forecasts. The existence of a common benchmark explains the decrease in forecast dispersion in the periods between earnings announcements. To formalize these findings, I develop a simple model of forecast-making processes under a common benchmark to explain the dynamics of forecast dispersion. My results highlight the importance of information selection as a driver of disagreement, especially in high-dimensional environments.

Abstract: We propose a new method to separately quantify investor disagreement and subjective uncertainty at the firm level using equity analyst forecasts. Our approach exploits heterogeneity in how forecast dispersion responds to the arrival of signals that are widely perceived as informative and interpreted homogeneously across agents. Intuitively, for a given level of disagreement in point forecasts, a larger post-signal compression in dispersion indicates greater ex-ante subjective uncertainty in investors’ beliefs. Using these measures, we document differences in the economic roles of disagreement and uncertainty. Subjective uncertainty rises sharply prior to crises, while disagreement peaks during and immediately after crises. In the cross-section, stocks with higher disagreement earn lower subsequent returns and exhibit higher trading volume. These effects are significantly attenuated when uncertainty is high. In contrast, higher uncertainty is associated with higher expected returns and lower trading volume. Stock return volatility is strongly related to disagreement but only weakly related to uncertainty. Finally, firm characteristics are more closely linked to disagreement than to uncertainty: Smaller firms, firms with lower profitability, and firms with higher R&D intensity exhibit systematically higher levels of disagreement.

Abstract: Geopolitical risk reaches a firm through multiple channels, so its economic significance depends not only on how saliently it is disclosed but also on how it is interrelated with a firm’s other risks. Using over three million risk factor disclosures from SEC 10-K filings between 2010 and 2024, we develop network-based measures of geopolitical risk along three dimensions: whether the firm’s geopolitical risk profile resembles the cross-sectional average, how closely geopolitical risk is connected to other risk topics, and whether geopolitical risk is linked to the firm’s most systemically important risk topics. First, we find significant cross-industry heterogeneity in how geopolitical risk is interrelated with other risk topics. However, environmental and cybersecurity risks are the two topics most strongly and consistently related to geopolitical risk. Second, a firm’s risk network structure moderates the effect of geopolitical risk on future investment and valuation. The investment decline is sharpest for firms whose geopolitical risk is connected to their most broadly interconnected risks and the valuation decline is largest for firms whose geopolitical risk reaches broadly across their other disclosed risks. Third, using the Russian invasion of Ukraine as a plausibly exogenous shock, we show that a significant geopolitical event can reconfigure firms’ risk networks. Firms whose geopolitical risk was more interrelated with natural-resource and macroeconomic risks pre-war were most likely to report war-attributed asset impairments. Overall, this paper highlights that researchers as well as practitioners should adopt a network-based conceptualization of geopolitical risk to account for its full impact.

Abstract: I develop firm-quarter measures of managers’ perceived risk and ambiguity from earnings call transcripts and study how these measures relate to corporate decisions and valuations. I distinguish risk, uncertainty the manager can characterize, from ambiguity, uncertainty she cannot. The two measures co-move with existing uncertainty proxies yet are far from collinear within a firm, implying that they capture distinct aspects of uncertainty. I find that the two measures relate to corporate policy along different margins. Risk predicts lower investment and lower net debt issuance, more so when the firm’s assets are harder to redeploy, consistent with deferring irreversible commitments. Ambiguity predicts a more liquid, but not larger, balance sheet: cash accumulates and leverage falls, consistent with preserving flexibility when waiting would not resolve the uncertainty. In valuation, risk also predicts a lower Tobin’s Q, through a decline in market value that exceeds the contraction in book assets, and higher ex-ante required returns. Ambiguity carries no comparable discount, and its ex-ante pricing attenuates with the firm’s buffer, suggesting that the market prices the response, not the exposure. Combining the two into a single uncertainty measure nets these opposite-signed responses, understating one and concealing the other.