Using survey data on expectations of stock returns, we recursively estimate the degree of extrapolative weighting in investors’ beliefs (DOX). In an extrapolation framework, DOX determines the relative weight investors place on recent-versus-distant returns. DOX varies considerably over time. The ability of price-scaled variables to predict the year-ahead equity premium is contingent on DOX. High price-scaled variables are followed by lower returns only when DOX is high. Our findings support extrapolation-based theories of the stock market and the interpretation of price-scaled variables as mispricing proxies. Our results help answer a critical question: when will an overvalued asset experience a correction?Received December 5, 2015; editorial decision June 22, 2017 by Editor Robin Greenwood.

We use exogenous variation in federal courts' composition, for instance due to a judge's death, as a quasi-natural experiment to study the equity value implications of court ideology. This design allows us to establish that firms experience an equity value loss when federal court ideology shifts in favor of plaintiffs and against corporations. The value loss stems from: (i) an increase in the expected costs of litigation; (ii) the deterioration of market-based governance mechanisms; (iii) and a perverse managerial incentive to decrease corporate disclosure in a heightened litigation environment.

We label the degree to which individuals are more optimistic at long horizons relative to short horizons as the horizon bias. We examine whether time-series variation in the horizon bias can explain the time-series variation in the equity term structure. We use analyst earnings forecasts to measure the degree of the horizon bias in the stock market. Consistent with the intuition from a stylized present value model, we find that periods of above-average horizon bias are associated with negative term premiums, whereas periods of below-average horizon bias are associated with positive term premiums.

We propose a latent-variables approach to recover extrapolative beliefs from asset prices. We estimate a present-value model of the price–dividend ratio of the market that embeds both return extrapolation and cash-flow extrapolation, alongside discount rates and rational expectations of dividend growth. This approach allows us to measure extrapolation bias without having to rely on survey data, and it inherently guarantees that the researcher focuses on a set of beliefs that matter for price formation. We show that extrapolative beliefs extracted from prices are highly correlated with surveys and that survey-based and price-based extrapolative beliefs share similar predictive properties for future returns, with the former improving upon the latter.