Jianfeng Yu

Uncertainty, Risk, and Incentives: Theory and Evidence

Uncertainty has qualitatively different implications than risk in studying executive incentives. We study the interplay between profitability uncertainty and moral hazard, where profitability is multiplicative with managerial effort. Investors who face greater uncertainty desire faster learning, and consequently offer higher managerial incentives to induce higher effort from the manager. In contrast to the standard negative risk-incentive trade-off, this “learning-by-doing” effect generates a positive relation between profitability uncertainty and incentives. We document empirical support for this prediction. n nThis paper was accepted by Wei Jiang, finance.

Dissecting the Profitability Premium

Previous studies show that the profitability-based factor can explain almost all asset pricing anomalies, highlighting the importance of firm profitability. This paper investigates both risk-based and behavioral-based explanations of the profitability premium itself. First, we show that the traditional macro risk is unlikely to be the source of the observed profitability premium. Second, the profitability premium exists primarily among firms with high arbitrage costs or high information uncertainty, and the majority of this premium is derived from the negative alpha of low profitability firms, consistent with the notion that overpricing is more prevalent than underpricing due to greater impediments to short. Third, we investigate the pattern of profitability premium at different holding horizons and find little evidence on long-run reversal, suggesting that the profitability premium is more likely to be related to underreaction, rather than ex-post overreaction. Finally, we compare three leading behavioral theories of over- and underreaction based on their different implications on the profitability premium, and our results suggest that inattention-induced underreaction is most plausible.

Optimal Long-Term Contracting with Learning

We introduce uncertainty into Holmstrom and Milgrom (1987) to study optimal long-term contracting with learning. In a dynamic relationship, the agents shirking not only reduces current performance but also increases the agents 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 decreases stochastically 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.

Lottery-Related Anomalies: The Role of Reference-Dependent Preferences

Previous empirical studies find that lottery-like stocks significantly underperform their nonlottery-like counterparts. Using five different measures of the lottery features in the literature, we document that the anomalies associated with these measures are statedependent: the evidence supporting these anomalies is strong and robust among stocks where investors have lost money, while among stocks where investors have gained profits, the evidence is either weak or even reversed. Several potential explanations for such empirical findings are examined and we document support for the explanation based on reference-dependent preferences. Our results provide a united framework to understand the lottery-related anomalies in the literature.

Impediments to Financial Trade: Theory and Measurement

We propose a tractable model of an informationally inefficient market. We show the equivalence between our model and a substantially simpler model whereby investors face distortive investment taxes depending both on their identity and the asset class. We use this equivalence to assess existing approaches to inferring whether individual investors have informational advantages. We also develop a methodology of inferring the magnitude of the frictions (implicit taxes) that impede financial trade. We illustrate the methodology by using data on cross-country portfolio holdings and returns to quantify these frictions, and locate the directions in which financial trade seems to be especially impeded. We argue that our measure of frictions contains useful information for the sources of failure of frictionless models, and it helps in studying whether certain factors (such as the size of the financial sector) are associated with lower financial frictions.

Characteristics-Based Factors

Recent studies have proposed a large set of powerful characteristics-based factors in the stock market. This study examines the pricing of these factors using portfolios that are formed by directly sorting stocks based on their exposure to these factors. These beta-sorted portfolios have very large ex post factor beta spreads. However, the return spreads between high- and low-beta firms are typically tiny and insignificant (on average, 0.01% per month). More important, we show that the differences between factor-adjusted returns and characteristics-adjusted returns for these beta-sorted portfolios are both economically and statistically significant at about 0.41% per month. In addition, factor-adjusted returns and characteristics-adjusted returns can be significantly different for a large number of anomalies and mutual funds. Our results thus urge cautions regarding the common practice of using factor models such as adjusting for investment style, performance evaluation, and performance attribution.

Aggregate Expected Investment Growth and Stock Market Returns

A bottom-up measure of aggregate investment plans, namely, aggregate expected investment growth (AEIG) can negatively predict market returns. At the one-year horizon, the adjusted in-sample R-square is 18.2% and the out-of-sample R-square is 14.4%. The return predictive power is robust after controlling for standard macroeconomic return predictors and proxies for investor sentiment. Further analyses suggest that the predictive ability of AEIG is at least partially driven by the time-varying risk premium. These findings lend support to neoclassical models with investment lags.

Short- and Long-Run Business Conditions and Expected Returns

Numerous studies argue that the market risk premium is associated with economic conditions and show that proxies for business conditions indeed predict aggregate market returns. By directly estimating short- and long-run expected economic growth, we show that short-run expected economic growth is negatively related to future returns, whereas long-run expected economic growth is positively related to aggregate market returns. At an annual horizon, short- and long-run expected growth can jointly predict aggregate excess returns with an R-sqr of 17-19%. Our findings indicate that the risk premium has both high- and low-frequency fluctuations and highlight the importance of distinguishing short- and long-run economic growth in macro asset pricing models.