Abstract: This paper develops a theory of the elasticity of preference for early resolution of uncertainty (PER) that parallels the Arrow-Pratt measure of risk aversion in expected utility theory. We demonstrate that the local welfare gain of early resolution of uncertainty is equal to the product of the elasticity of PER and the conditional variance of continuation utility. We illustrate how asset market data can be used to estimate the elasticity of PER and how this measure can be used to compute the welfare gain for various experiments of early resolution of uncertainty.

Abstract: The U.S. stock market return during the first month of a quarter positively predicts the second month's return, which then negatively predicts the first month's return of the next quarter. The pattern arises because investors do not fully recognize that earnings announced in the second month of a quarter are inherently similar to those announced in the first month, and thereby overreacting to such predictably repetitive earnings.  The same pattern exists in the cross-section of industry returns.  Evidence from survey data lends support to the mechanism of correlation neglect.

Abstract: We introduce forecast-agnostic (FA) portfolios that exhibit out-of-sample market-timing ability without relying on estimated predictive coefficients. These portfolios go long or short the market based on the level of a predictor variable, thereby avoiding the instability and estimation error that undermine traditional market-timing strategies. Despite using predictor variables that typically deliver negative out-of-sample R2 values (Goyal, Welch, Zafirov 2024), FA portfolios deliver significantly positive alphas on average. We explain these seemingly contradictory phenomena by interpreting regression coefficients as portfolio returns: genuine predictability is necessary for high portfolio returns, whereas achieving a positive out-of-sample R2 additionally requires the ability to forecast the returns on the forecast-agnostic portfolios themselves. As these FA portfolio returns could not be too predictable, estimating them substantially penalizes the out-of-sample R2 by the inverse of the estimation sample size. Simulations show that the statistic we propose has power to detect predictability that extends beyond in-sample diagnostics and the out-of-sample R2.

Abstract: This paper documents a robust and significant industry component of the financial distress anomaly. The industry distress anomaly remains significant after controlling for the within-industry firm distress anomaly, yet becomes insignificant in hypothetical industries constructed by reshuffling firms across real industries. To rationalize the industry distress anomaly, we propose an industry equilibrium model with endogenous strategic competition. Central to the model is the competition-distress feedback within industries, which amplifies the exposure of industries’ profit margins and equity returns to aggregate discount-rate shocks. Industries with higher idiosyncratic left-tail risks are more distressed, yet are endogenously less exposed to aggregate shocks due to the weaker competition-distress feedback, implying lower expected equity returns.