We develop a structural theory of beliefs and behavior, that relaxes the assumption of time consistency in beliefs. Our theory is based on the trade-off between optimism, which raises anticipatory utility, and objectivity, which promotes efficient actions. We present it in the context of allocating work on a project over time, develop testable implications to contrast it with models assuming time-inconsistent preferences, and compare its predictions to existing evidence on behavior and beliefs. Our predictions are: (i) optimal beliefs are optimistic and time-inconsistent; (ii) incentives can affect beliefs and behavior; (iii) in the presence of a commitment device, people optimally exhibit preference for commitment.

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We use novel data on individual activity in a sports betting market to study the effect of past performance sequences on individual behavior in a real market. The revelation of fundamental values in this market enables us to disentangle whether behavior is caused by sentiment or by superior information about market mispricings, hence to cleanly test in a real setting two sentiment-based theories of momentum and reversals—the regime-shifting model of Barberis, Shleifer, and Vishny (1998) and the gambler’s/hot-hand fallacy model of Rabin (2002). Furthermore, our long panel allows us to calculate the proportions of individuals who exhibit each type of behavior. We find that i) three quarters of individuals exhibit trend-chasing behavior; ii) seven times as many individuals exhibit behavior consistent with Barberis, Shleifer, and Vishny (1998) as exhibit behavior consistent with Rabin ( 2002); and iii) no individuals earn superior returns from momentum trading.

Barras, Scaillet, Wermers (2010) propose the False Discovery Rate to separate skill (alpha) from luck in fund performance. Using simulations with parameters informed by the data, we find that this methodology is overly conservative and underestimates the proportion of nonzero-alpha funds. E.g., 65% of funds with economically large alphas of ±2% are misclassified as zero-alpha. This bias arises from the low signal-to-noise ratio in fund returns and the consequent low statistical power. Our results raise concerns regarding the FDR’s applicability in performance evaluation and other domains with low power, and can materially change its conclusion that most funds have zero alpha.

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Using trading data from a sports-wagering market, we estimate individuals' dynamic risk preferences within the prospect-theory paradigm. This market’s experimental-like features facilitate preference estimation, and our long panel enables us to study whether preferences vary across individuals and depend on earlier outcomes. Our estimates extend support for experimental findings—mild utility curvature, moderate loss aversion, and probability overweighting of extreme outcomes—to a market setting and reveal that preferences are heterogeneous and history-dependent. Applying our estimates to a portfolio choice problem, we show prospect theory can better explain the prevalence of the disposition effect than previously thought.

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We propose a novel methodology that jointly estimates the proportions of skilled/unskilled funds and the cross-sectional distribution of skill in the mutual fund industry. We model this distribution as a three-component mixture of a point mass at zero and two components—one negative, one positive—that we estimate semi-parametrically. This generalizes previous approaches and enables information-sharing across funds in a data-driven manner. We find that the skill distribution is non-normal (asymmetric and fat-tailed). Furthermore, while the majority of funds have negative alpha, a substantial 13% generate positive alpha. Our approach improves out-of-sample portfolio performance and significantly alters asset allocation decisions.

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We construct novel measures of mutual funds’ environmental, social, and governance (ESG) commitment by analyzing the discretionary investment-strategy descriptions of their prospectuses. We find that fund flows respond strongly to text-based ESG measures. Using discrepancies between text- and fundamentals-based ESG measures, we identify greenwashing funds. We find that greenwashing is more prevalent since 2016 (coinciding with the Paris Agreement) and among funds with lower past flows and higher expense ratios, and isn’t associated with superior subsequent performance. Furthermore, greenwashers attract similar flows to genuinely green funds, suggesting that investors cannot distinguish them. Our results could help regulators’ efforts to combat ESG-related misconduct.

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While it is commonly accepted that risk preferences differ across individuals, studies that estimate them typically allow for limited heterogeneity. We develop a methodology that allows for richer representation of heterogeneity both within and across utility types characterized by different behavioral features. This enables us to improve individual- and population-level estimates, and to assess the relative importance of loss aversion and probability weighting, and their prevalence in the population. Applying our model to individual sports-betting choices, we find that utility curvature alone does not explain observed choices and, while two-thirds of individuals exhibit loss aversion, all exhibit probability weighting.

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We study the home bias using individual-level data from an online sports-betting market. Contrary to other markets where home bias is confounded by institutional and information frictions, our market’s experimental-like features enable us to test cleanly whether the psychological drivers of the home bias are strong enough to survive significant welfare costs. We find that individuals exhibit a bias toward home teams, which does not yield superior performance but distorts portfolios, generating welfare costs of similar magnitude as in the stock market. Our findings help solidify the foundation of the behavioral explanation of the home bias in other real markets.

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We construct a unique 10-year panel dataset that contains an experience measure for the directors of 650 large corporations in the U.S., and investigate the marginal effect of board experience on firm performance. Our findings are the following: 1) Firms with more experienced independent directors experience higher abnormal returns and consistently beat analysts’ earnings forecasts. 2) They have a lower covariance with the Fama-French HML factor and a lower probability of bankruptcy, as measured by Altman’s z-score. 3) They engage in less earnings manipulation as measured by fewer negative income restatements and lower accounting accruals. This evidence indicates not only that board experience has positive marginal monitoring (and possibly advisory) value, but also that both firms and the market fail to recognize this potential value. Our results are robust to the use of OLS fixed-effects and Instrumental Variables using lag transformations as instruments, which, to varying degrees help alleviate concerns that they are driven by unobserved firm heterogeneity, selection bias, and/or measurement error. Performing IV estimations that utilize successively deeper lags as instruments, we find that our results are robust to the presence of some serial correlation in the disturbance; while testing for serial correlation, we find evidence that it is both limited in horizon and small in magnitude.

We study the existence and impact of search frictions in the market for corporate control in order to explain who makes acquisitions. We proxy search frictions with the board’s degree of connectedness, and also with measures of geographic proximity and business similarity. Additionally, we take into account measures of market thickness since they amplify the effect of such frictions, and also management incentives, in particular golden parachute provisions. Using data from 1990 to 2006, we find that firms are more likely to be acquirers (targets) when search frictions are low (high), there are more firms available to buy, and a golden parachute is not (is) provided to the firm’s manager. These findings are largely consistent with predictions from the recent theoretical literature that models the decision of firms to actively search for potential targets, in a market-with-frictions setting. We alleviate concerns that these results are driven by firm heterogeneity or selection bias, by showing that they are robust to the use of OLS with firm-level fixed effects and instrumental variables estimation. Finally, we find that the provision of golden parachutes increases the average acquirer abnormal return by 2.5% whereas it does not significantly impact target premia; and that search frictions only affect target premia.