General Partners (GPs) in private equity face a trade-off between focusing their skills and effort on fewer investments to earn higher returns, or investing more broadly to reduce risk through diversification. Using a novel, deal-level dataset of 5,925 global investments from 1999 to 2016, we...

To examine how financial education affects financial outcomes, one must evaluate whether and how sample selection may bias inferences regarding program impacts. Our incentivized experiment reveals how such selection influences estimated financial education effects. The more financially literate...

We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

Machine learning methods in asset pricing are often criticized for their black box nature. We study this issue by predicting corporate bond returns using interpretable machine learning on a high-dimensional bond characteristics dataset. We achieve state-of-the-art performance while maintaining...

We evaluate private equity (PE) performance using investor-specific stochastic discount factors, and examine whether investors could benefit from changing their allocation to PE. Plans invest in PE funds with higher average risk-adjusted performance. This is mainly due to access to successful PE...

We propose a model that starts from the premise that intangible capital needs to be stored on some medium --- software, patents, essential employees --- before it can be utilized in production. Storage implies that intangible capital may be partially non-rival within the firm, leading to scale...

We study the effects of broadband internet use on the investment decisions of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market...

Portfolio optimization focuses on risk and return prediction, yet implementation costs critically matter. Predicting trading costs is challenging because costs depend on trade size and trader identity, thus impeding a generic solution. We focus on a component of trading costs that applies...

A number of papers have solved for the optimal dynamic portfolio strategy when expected returns are time-varying and trading is costly, but only for agents with myopic utility. Non-myopic agents benefit from hedging against future shocks to the investment opportunity set even when transaction...

We analyze the financial performance of a hypothetical portfolio of 120 mRNA vaccine candidates in the preclinical stage targeting 11 emerging infectious diseases. We calibrate the simulation parameters with input from domain experts in mRNA technology and an extensive literature review. We find...