We introduce uncertainty into Holmstrom and Milgrom (1987) to study optimal long-term contracting with learning. In a dynamic relationship, the agent's shirking not only reduces current performance, but also increases the agent's information rent due to the persistent belief manipulation effect. We characterize the optimal contract using the dynamic programming technique in which information rent is the unique state variable. In the optimal contract, the optimal effort is front-loaded and stochastically decreases over time. Furthermore, the optimal contract exhibits an option-like feature in that incentives increase after good performance. Implications about managerial incentives and asset management compensations are discussed.

We propose a tractable model of an informationally inefficient market featuring nonrevealing prices, general preferences and payoff distributions, but not noise traders. We show the equivalence between our model and a substantially simpler one in which investors face distortionary investment taxes depending on both their identity and the asset class. This equivalence allows us to account for such phenomena as underdiversification. We further employ the model to assess approaches to performance evaluation and find that it provides a theoretical basis for some intuitive practices, such as style analysis, that have been adopted by finance professionals.

We propose a unified model of limited market integration, asset-price determination, leveraging, and contagion. Investors and firms are located on a circle, and access to markets involves participation costs that increase with distance. Due to a complementarity between participation and leverage decisions, the equilibrium may exhibit diverse leverage and participation choices across investors, although investors are ex ante identical. Small changes in market-access costs can cause a change in the type of equilibrium, leading to discontinuous price changes, deleveraging, and portfolio-flow reversals. Moreover, the market is subject to contagion—an adverse shock to investors in some locations affects prices everywhere.

Motivated by psychological evidence on limited investor attention and anchoring, we propose two proxies for the degree to which traders under- and overreact to news, namely, the nearness to the Dow 52-week high and the nearness to the Dow historical high, respectively. We find that nearness to the 52-week high positively predicts future aggregate market returns, while nearness to the historical high negatively predicts future market returns. We further show that our proxies contain information about future market returns that is not captured by traditional macroeconomic variables and that our results are robust across G7 countries. Comprehensive Monte Carlo simulations and comparisons with the NYSE/Amex market cap index confirm the significance of these findings.

This study shows the influence of investor sentiment on the market's mean–variance tradeoff. We find that the stock market's expected excess return is positively related to the market's conditional variance in low-sentiment periods but unrelated to variance in high-sentiment periods. These findings are consistent with sentiment traders who, during the high-sentiment periods, undermine an otherwise positive mean–variance tradeoff. We also find that the negative correlation between returns and contemporaneous volatility innovations is much stronger in the low-sentiment periods. The latter result is consistent with the stronger positive ex ante relation during such periods.

We study the asset‐pricing implications of technological growth in a model with “small,” disembodied productivity shocks and “large,” infrequent technological innovations, which are embodied into new capital vintages. The technological‐adoption process leads to endogenous cycles in output and asset valuations. This process can help explain stylized asset‐valuation patterns around major technological innovations. More importantly, it can help provide a unified, investment‐based theory for numerous well‐documented facts related to excess‐return predictability. To illustrate the distinguishing features of our theory, we highlight novel implications pertaining to the joint time‐series properties of consumption and excess returns.

This paper studies the cross-sectional risk–return trade-off in the stock market. A fundamental principle in finance is the positive relation between risk and expected return. However, recent empirical evidence suggests the opposite. Using several intuitive risk measures, we show that the negative risk–return relation is much more pronounced among firms in which investors face prior losses, but the risk–return relation is positive among firms in which investors face prior gains. We consider a number of possible explanations for this new empirical finding and conclude that reference-dependent preference is the most promising explanation.

Extremely long odds accompany the chance that spurious-regression bias accounts for investor sentiment׳s observed role in stock-return anomalies. We replace investor sentiment with a simulated persistent series in regressions reported by Stambaugh, Yu, and Yuan (2012), who find higher long-short anomaly profits following high sentiment, due entirely to the short leg. Among 200 million simulated regressors, we find none that support those conclusions as strongly as investor sentiment. The key is consistency across anomalies. Obtaining just the predicted signs for the regression coefficients across the 11 anomalies examined in the above study occurs only once for every 43 simulated regressors.

This study explores the role of investor sentiment in a broad set of anomalies in cross-sectional stock returns. We consider a setting in which the presence of market-wide sentiment is combined with the argument that overpricing should be more prevalent than underpricing, due to short-sale impediments. Long-short strategies that exploit the anomalies exhibit profits consistent with this setting. First, each anomaly is stronger (its long-short strategy is more profitable) following high levels of sentiment. Second, the short leg of each strategy is more profitable following high sentiment. Finally, sentiment exhibits no relation to returns on the long legs of the strategies.

Investor preferences for holding speculative assets are likely to be more pronounced ahead of firms’ earnings announcements, probably because of lower inventory costs and immediate payoffs or because of enhanced investor attention. We show that the demand for lottery-like stocks is stronger ahead of earnings announcements, leading to a price run-up for these stocks. In sharp contrast to the standard underperformance of lottery-like stocks, lottery-like stocks outperform non-lottery stocks by about 52 basis points in the 5-day window ahead of earnings announcements. However, this return spread is reversed by 80 basis points in the 5-day window after the announcements. Moreover, this inverted-V-shaped pattern on cumulative return spreads is more pronounced among firms with a greater retail order imbalance, among firms with low institutional ownership, and in regions with a stronger gambling propensity, and it is also robust after controlling for past 12-month returns and various proxies for investor attention.