Abstract: Using valuation reports disclosing perceived cashflow growth (g) and discount rates (k) in M&A transactions, we examine what managers learn from target stock prices. Before correcting for endogeneity, both appear sensitive to prices—positively for g, negatively for k, and with equal magnitude—suggesting managers learn about both. However, using noise in prices as an instrument, only k reacts—with corrected estimates indicating that 89% of managers’ information about k comes from prices. Therefore, stock markets provide insights into risk and the compensation it requires, but not cashflows, which managers already understand well. Cross-sectional tests reinforce this conclusion.
Discussant: Ricardo Delao, University of Southern California
Abstract: We examine how large asset managers form and justify long-horizon beliefs by analyzing their Capital Market Assumptions (CMAs)—articulated through tables, figures, and narratives. We develop a novel method that transforms CMA text narratives into quantifiable causal networks using large language models, capturing both the complexity of managers’ mental models and their allocation of attention across macro-financial topics. Our analysis reveals substantial heterogeneity in asset managers’ beliefs, both quantitative and narrative. Using granular numerical data on the building blocks of managers' return expectations, we identify multiple drivers of cross-sectional dispersion in expectations. Text-based measures show that the average coefficient of variation in cognitive complexity exceeds 0.7, while that in topic attention exceeds 1, indicating pronounced dispersion in both how managers reason and how they allocate attention to economic relationships. We further document systematic biases in asset managers’ beliefs using both quantitative and textual evidence. Return expectations deviate predictably from objective benchmark forecasts: greater cognitive complexity is associated with larger ex-ante forecast errors, and differences in attention to key building blocks affect the degree of over- or underreaction. Finally, we find evidence of historically anchored expectations in second moments. Overall, while institutional expectations are economically meaningful and linked to objective return predictors, they nonetheless exhibit systematic and predictable deviations from objective benchmarks.
Discussant: Philippe van der Beck, Harvard University
Christian Heyerdahl-Larsen, BI Norwegian Business School
Philipp Illeditsch, Texas A&M University
Petra Sinagl, University of Iowa
Abstract: Recessions cause substantial but delayed drops in output, followed by recoveries with abnormally high growth. We propose a new theory where the awareness of new risks negatively impacts growth, leading to recessions of varying duration and severity. Our model showsthat risk premia and return volatilities exhibit a hump-shaped pattern at the onset of recessions, not rising immediately, unlike in most non-expected utility models (Ai and Bansal, 2018). These results align with empirical patterns of output, risk premia, and volatilities observed during recessions. Hence, our model explains a stronger link between fundamentals and asset prices observed during recessions and recoveries.
Discussant: Aditya Chaudhry, Ohio State University
Abstract: We hypothesize that most individuals have little understanding of how the distribution of equityreturns evolves over horizons. As a result, individuals compress their estimates of near- (1-year)and long-term (10-year) uncertainty. Consistent with our hypothesis, individuals report estimatesthat imply an implausibly strong negative relation between risk and horizon when askedabout total returns but estimates that imply an implausibly strong positive relation betweenrisk and horizon when asked about average returns. The analysis helps explain puzzling resultsacross several literatures and has implications for household finance, corporate finance, and assetpricing.
Discussant: Xindi He, Georgia Institute of Technology
