Knowledge that Transforms

During the U.S. housing credit boom, publicly traded banks increased mortgage lending activity and relaxed standards much more than privately held banks. The increase in risk had real effects for a variety of county-level aggregates including employment and consumption. Cross-sectional evidence and a quasi-experiment indicate that the increase in risk stemmed from the institutional ownership and the equity compensation of publicly traded banks, in turn leading banks to place greater weight on short-term equity performance. These results are consistent with the view that a focus on short-term earnings and stock prices amplifies boom–bust credit cycles, in turn leading to real cycles for the aggregate economy.

During the 2020–2021 “AAPI Hate,” mutual funds led by female managers perceived as East Asian underperformed relative to other female managers. This effect is stronger in states with higher anti-Asian animus, among more actively managed funds, and when these managers hold sole or senior roles. Factors concurrent with COVID-19, including childcare challenges, concerns for overseas families, marketplace and workplace discrimination, and exposure to the Chinese economy, cannot explain the effect. Underperformance is traceable to poor stock picking due to impairments in generating private information. Racial-ethnic animosity, even outside workplace or marketplace, hinders productivity and decision-making in high-skill professions.

To understand the dynamics of investors’ asset demands, we develop a general-equilibrium model driven by a single latent variable: heterogeneity in investors’ confidence about mean endowment growth. The model predicts persistent heterogeneity in asset demands and concentrated portfolios. Consistent with the data, limited confidence reduces investors’ demand elasticities and makes stock prices excessively volatile—driven by latent demand rather than observable characteristics. The underlying economic mechanisms are driven primarily by investors’ desire to hedge changes in future beliefs instead of current disagreement. Finally, consistent with survey data, investors’ expectations correlate positively with past returns and negatively with future returns.

Numerous trading strategies examined in options research exhibit remarkably high mean returns and Sharpe ratios. We show some of these seemingly “good deals” are due to look-ahead biases. These biases stem from using information unavailable at the portfolio formation time to filter out observations suspected of being noisy or erroneous. Our results suggest that elevated Sharpe ratios may serve as potential indicators of such look-ahead biases. Furthermore, deviating from previous literature findings, we show that illiquidity is not strongly priced in stock options and that only a small set of stock characteristics are in fact associated with option expected returns.

We examine how portfolio regulations affect risk sharing between financial institutions with market power. Unconstrained access to complete markets permits flexible exploitation of market power and induces inefficient risk sharing. Appropriate portfolio restrictions counteract this, improving liquidity and risk sharing by bundling securities with offsetting strategic incentives. However, excessive regulation can be counterproductive, destroying gains from trade. An application of our theory shows that cross-asset spillovers are critical for policy evaluation: in general equilibrium, risk sharing can improve even if certain asset-specific liquidity measures deteriorate. We also discuss the effects of asymmetric regulation for different institutions.

We study intermediation in the housing market. Using data from an online platform utilized by real estate agents to generate leads, we identify exogenous intermediary attention arising from the quasi-randomized ordering of potential listings. Greater intermediary attention leads to an increased probability of listing with an agent and selling quickly, and a higher transaction price. The listing and transaction probabilities of neighboring properties decrease in intermediary attention. These results contrast sharply with endogenous correlations and provide causal evidence that intermediaries resolve property-level frictions deriving from search, information, or behavioral considerations but do not mitigate neighborhood-level information asymmetries.

Many regulations aim to promote coordination among creditors in bankruptcy by ex post restricting their ability to exit distressed firms. However, such restrictions may harm creditors’ ex ante incentives to stay invested, thereby worsening coordination outcomes. We build a dynamic coordination model to show how this force shapes creditor runs, bankruptcy filings, and regulation designs. Intriguingly, filing for bankruptcy early, thereby preserving more assets for latecomers, can prolong firm life. Furthermore, regulators’ clawbacks on prebankruptcy repayments can be superior to firms’ commitment to early bankruptcy filing. Our analysis generates implications for automatic stay, avoidable preference, bank failures, and seniority structure.

Using confidential microdata, we show that shocks to primary dealers’ constraints have significant effects on the U.S. Treasury securities market. We consider two types of constraints: the supplementary leverage ratio and trading desk value-at-risk constraints. In response to tighter constraints, dealers reduce their Treasury positions, triggering a reduction in aggregate turnover and an increase in dealer intermediation margin. Impaired intermediation also amplifies the yield response to net demand shifts and weakens Treasury auction outcomes. Our estimates suggest that the (shadow) cost of dealer constraints is as high as 9% of dealers’ profit margins.

We study how terminated correspondent banking relationships affect international trade. Drawing on firm-level export data from emerging Europe, we show that when local banks lose access to correspondent services, their corporate clients, especially small- and medium-sized enterprises, experience significant export declines. Firms only partially offset lost exports with higher domestic sales, resulting in lower total revenues and employment. Other firms cease operations entirely. These firm-level impacts aggregate to lower product-level exports from countries more exposed to correspondent bank retrenchment.

We propose a statistical model of heterogeneous beliefs wherein investors are represented as different machine learning model specifications. Investors form return forecasts from their individual models using common data inputs. We measure disagreement as forecast dispersion across investor-models (MFD). Our measure aligns with analyst forecast disagreement but more powerfully predicts returns. We document a large and robust association between belief disagreement and future returns. A decile spread portfolio that sells stocks with high disagreement and buys stocks with low disagreement earns a value-weighted return of 13% per year. Further analyses suggest MFD-alpha is mispricing induced by short-sale costs and limits-to-arbitrage.