We analyze a model in which an anomaly is unknown to arbitrageurs until its discovery, and test the model implications on both asset prices and arbitrageurs’ trading activities. Using data on 99 anomalies documented in the existing literature, we find that the discovery of an anomaly reduces the correlation between the returns of its decile-1 and decile-10 portfolios. This discovery effect is stronger if the aggregate wealth of hedge funds is more volatile. Finally, hedge funds increase (reverse) their positions in exploiting anomalies when their aggregate wealth increases (decreases), further suggesting that these discovery effects operate through arbitrage trading.

Sophisticated investors frequently choose to publicly disclose private information, a phenomenon inconsistent with most theories of speculation. We propose and test a model to bridge this gap. We show that when a speculator cares about both short-term portfolio value and long-term profit, a disclosure mixing asset fundamentals and her holdings is optimal by inducing competitive dealership to revise prices toward those holdings while alleviating adverse selection. We find that when mutual fund managers have stronger short-term incentives, the frequency of strategic non-anonymous disclosures about their stocks by market-worthy newspaper articles increases and those stocks’ liquidity improves, consistent with our model.

We demonstrate the benefits of merging traditional hypothesis-driven research with new methods from machine learning that enable high-dimensional inference. Because the literature on post-earnings announcement drift (PEAD) is characterized by a “zoo” of explanations, limited academic consensus on model design, and reliance on massive data, it will serve as a leading example to demonstrate the challenges of high-dimensional analysis. We identify a small set of variables associated with momentum, liquidity, and limited arbitrage that explain PEAD directly and consistently, and the framework can be applied broadly in finance.

Using detailed data on U.S. households’ locations, employment, and financial portfolios, we document that individuals employed in locally clustered industries are more likely to invest in risky assets. This pattern is strongest among individuals with high labor income, employed in skilled occupations, and with strong cognitive skills. Our overall evidence suggests the relation between industry clusters and investment decisions is best explained by clusters enhancing human capital among local industry workers, in turn amplifying their effective risk tolerance. Our findings highlight the important role of local labor market composition in generating household portfolio patterns within and across geographies.

We introduce a new approach to estimating long-term aggregate discount rates using the cross section of earnings and book values to explain current stock prices and extract expected market returns. The proposed discount rate measure is countercyclical. Shocks to it account for nearly half of historical market return variation; in contrast, shocks to other discount rate measures account for no more than 2%. It dominates other measures in explaining time-series variation in returns on duration-sorted portfolios and delivers out-of-sample predictability that exceeds that afforded by other expected return measures and predictive variables. It also performs well in international equity markets.

We explore the effects of online customer ratings on financial policy. Using a large sample of Parisian restaurants, we find a positive and economically significant relationship between customer ratings and restaurant debt. We use the locally exogenous variations in customer ratings resulting from the rounding of scores in regression discontinuity tests to establish causality. Favorable online ratings reduce cash flow risk and increase resilience to demand shocks. Consistent with the view that good online ratings increase the debt capacity of restaurants and their growth opportunities, restaurants with good ratings use their extra debt to invest in tangible assets.

We develop a dynamic model of corporate investment and financing, in which shocks to the value of collateralizable assets generate variation in firms’ debt capacity. We show that the degree of similarity among firms’ financial flexibility forecasts cross-sectional variation in return correlation. We test the implications of the model with firm-level data in two empirical analyses using i) an instrumental variable approach based on shocks to the value of collateralizable corporate assets and ii) the outbreak of the COVID-19 crisis as an event study. We find that firms in the same percentile of the cross-sectional distribution of financial flexibility have 62% higher correlation in stock-return residuals than firms 50 percentiles apart.

We show that a common component governs volatility dynamics across a wide range of traded equity factors. This “common factor volatility” (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. CFV allows us to characterize stochastic discount factor (SDF) volatility dynamics in a very general sense and we show that many popular models imply SDFs with time-varying volatility that correlates strongly with CFV.

This study introduces a new measure of ex ante litigation risk using scrutiny of SEC filings by the source of securities litigation (plaintiffs’ lawyers) to reduce measurement error, relative to existing measures. We show that plaintiff-lawyer views proxy for the largely unobservable factors that make firms more likely to face litigation risk. Lagged views precede the public bad news revelation that triggers litigation and predicts future realized litigation risk (i.e., securities class actions filings and plaintiff-lawyer investigations) and stock market outcomes. Finally, we provide new insights into the plaintiff-lawyer case selection process that otherwise cannot be observed.

This article analyzes the optimal allocation of losses via a Central Clearing Counterparty (CCP) in the presence of counterparty risk. A CCP can hedge this risk by mutualizing losses among its members. This protection, however, weakens members’ incentives to manage counterparty risk. Delegating members’ risk monitoring to the CCP alleviates this tension in large markets. To discipline the CCP at minimum cost, members offer the CCP a junior tranche and demand capital contribution. Our results endogenize key layers of the default waterfall and deliver novel predictions on its composition, collateral requirements, and CCP ownership structure.

Yes. We show that aggregate stock returns predict aggregate U.S. employment, despite the industrial composition of publicly traded firms differing markedly from that of all firms, and the representativeness of public firms declining over time. We also show that appropriately reweighted stock returns predict industry and local labor market outcomes. We find the strongest evidence of an alignment of interests between shareholders and workers in the manufacturing sector, despite its declining labor share of output. Our findings suggest that at quarterly frequencies, product demand shocks are more important drivers of industry- and city-level stock returns than technology shocks.

Combining experimental data sets from seven individual studies, including 255 asset markets with 2,031 participants, and 36,326 short-term price forecasts, we analyze the role of heterogeneity of beliefs in the organization of trading behavior by reproducing and reconsidering earlier experimental findings. Our results confirm prior evidence that price expectations affect trading behavior. However, heterogeneity in beliefs does not seem to drive overpricing and asset market bubbles, as suggested by earlier studies, and we find no indication of short-term beliefs being better determinants of trading behavior than longer-term beliefs.

We argue that syndicates associate venture capitalists (VCs) with uneven skill levels in order to lower their expected gains from threatening to stop financing: Non-continued participation would send a milder negative signal to alternative financiers. This can explain the empirical observations that i) early-round syndicates regularly associate VCs with different levels of experience and ii) follow-on syndicates often involve none of the early-round VCs. Consistent with the theory, we find empirically that the heterogeneity of VC experience levels in a syndicate is i) negatively related to the extent to which the founders of the VC-backed firm are professionally well connected and ii) positively related to the likelihood of syndicate switching in a later round.

Analyzing 48 foreign exchange (FX) rates and 1.2 million FX-related news articles over a 35-year period, using digital textual analysis, we find that a currency reversal investment strategy that buys (sells) currencies with low (high) media sentiment offers strong positive and statistically significant returns and Sharpe ratios. The results are robust and the strategy adds value over other currency premia determinants. Analysts’ forecasts systematically mispredict the reversal strategy. This is the first article to show that price reversals based on media sentiment are a well-defined feature of the FX market.

Using an international sample of IPO firms and two country-level measures of financial literacy, we find strong evidence that financial literacy is negatively associated with IPO underpricing. In cross-sectional analyses, we find that the effect of financial literacy in reducing IPO underpricing is more pronounced when the information environment is less transparent. Employing path analysis, we document that information friction, firm transparency, and stock market participation are mechanisms that mediate this relationship. Our study contributes to and extends the literature by providing strong evidence that citizens’ financial literacy has an important and consistent influence on IPO underpricing.