Knowledge that Transforms

This paper documents that U.S. equity returns are large and positive during the opening hours of European markets. These returns are pervasive and highly economically and statistically significant. Consistent with models of inventory risk, we demonstrate a strong relationship with order imbalances at the close of the preceding U.S. trading day. Rationalizing unconditionally positive “overnight drift” returns, we uncover an asymmetric reaction to demand shocks: market sell-offs generate robust positive overnight reversals, while reversals following market rallies are much more modest. We argue that demand shock asymmetry can arise in inventory management models with time-varying market maker risk-bearing capacity.

We estimate unsmoothed private equity net asset values (NAVs) at weekly frequency for individual funds. Using simulations and large samples of buyout and venture funds, we show that our method yields superior estimates of NAVs relative to simple approaches based on extrapolation of reported NAVs. The market beta of an average buyout (venture) fund is around 1.0 (1.4), and the total risk is 33% (40%) per year. The risk-return profile of the funds varies significantly over time and across funds. Risk-taking and reporting quality appear to persist by manager.

We quantify the real implications of trade-offs between firm information disclosure and long-term investment efficiency. We estimate a dynamic equilibrium model in which firm managers confront realistic incentives to misreport earnings and distort their real investment choices. The model implies a socially optimal level of disclosure regulation that exceeds the estimated value. Counterfactual analysis reveals that eliminating earnings misreporting completely through disclosure regulation incentivizes managers to distort real investment. Lower earnings informativeness raises the cost of capital, which results in a 5.7% drop in average firm value, but more modest effects on social welfare and aggregate growth.

This study provides novel evidence regarding the effects of loan-to-value (LTV) limits on housing choices. Using a detailed loan-level dataset, I exploit the introduction of LTV limits in Israel. I find that the LTV limits led borrowers to choose housing units that were more affordable, farther from the central business district, and in lower socioeconomic neighborhoods. Additionally, these LTV limits increase interest rates and decrease loan amounts. The findings of this study indicate that macroprudential policies, which focus on the stability of the financial system, have micro implications on location choices, commuting costs, and movement to less-advantaged areas.

Combining novel data on analyst employment history and mutual fund commission payments, we show that client funds generate higher returns on stocks for which they have access to research by industry expert analysts. The outperformance is greater when funds are more important clients and cannot be attributed to tipping. Client funds place modestly higher weights on stocks covered by industry expert analysts and allocate more commissions to brokers providing such coverage. For identification, we exploit exogenous analyst coverage disruptions. Our findings contribute to the debate on whether mutual funds obtain any investment value from access to analysts through the soft-dollar arrangement.

We examine whether shareholder votes in environmental and social (ES) proposals are informative about firms’ ES risks. ES proposals are unique in that they nearly always fail. We examine whether mutual funds’ support for these failed proposals contains information about the ES risks that firms face. Higher support in failed ES proposals predicts subsequent ES incidents and the effects of these incidents on shareholder value. Examining the detailed records of fund votes, we find that agency frictions between a group of shareholders contribute to proposal failure.

A duty of loyalty prohibits fiduciaries from appropriating business opportunities from their companies. Starting in 2000, Delaware, followed by several other states, allowed boards to waive their duty. We show that public firms covered by waiver laws invest less in R&D, produce fewer and less valuable patents, and exhibit abnormally high inventor departures. Remaining innovation activities contribute less to firm value, a fact confirmed by the market reaction when firms reveal their curtailed internal growth opportunities by announcing acquisitions. Consistent with the laws’ intent to provide contracting flexibility to emerging firms, we find evidence of positive impacts for small firms.

Using satellite imagery of retail firms’ parking lots to measure time-varying local firm-specific performance, we document that analysts incorporate local information into their forecasts. Analysts rely more on local signals when less firm-wide information is available. This incorporation of noisy local firm information has firm-level implications. Examining across industries, we find causal evidence that geographic concentration of analysts increases consensus forecast errors and decreases firm liquidity. These effects are stronger for harder-to-value stocks. The market values geographic firm information, as the abnormal return around forecast revisions is higher for analysts who cover a firm from a unique location.

We study the speed with which investors learn about managers’ skills by examining how quickly investor and managers’ beliefs converge. After showing our measure proxies for the change in the dispersion of beliefs, we find that hedge fund investors learn as fast as suggested by Bayes’ rule. However, we find mutual fund investors learn more slowly than suggested by Bayes’ rule. Mutual fund investors’ slow learning is not due to the use of different performance measures, institutional frictions, or lack of sophistication, but could be due to a low payoff from learning. Our results indicate learning speed depends on financial participants’ incentives.

Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management. This is the first study exploring the feedback effect on corporate disclosure in response to technology.