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...

In recent years, impact investors - private investors who seek to generate simultaneously financial and social returns - have attracted intense interest and controversy. We analyze a novel, comprehensive data set of impact and traditional investors to assess how the non-financial characteristics...

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...

Do returns in private equity (PE) rise or fall with fund scale? This question is increasingly urgent amid larger funds and new focus on the retail market. Since better managers can raise larger funds, the causal effect is difficult to identify. We develop an instrument based on gifts to...

We propose a unified theory of asset price determination encompassing both "conventional" and "alternative" asset classes (private equity, real estate, etc.). The model features disruption of old by young firms and skewness in the distribution of innovative rents among the young innovators. The...

We document that the convenience yield of U.S. Treasuries exhibits properties that are consistent with a hedging perspective of safe assets. The convenience yield tends to be low when the covariance of Treasury returns with the aggregate stock market returns is high. A decomposition of the...

We survey the growing literature emphasizing the role that supply-and-demand forces play in shaping the term structure of interest rates. Our starting point is the Vayanos and Vila (2009, 2021) model of the term structure of default-free bond yields, which we present in both discrete and...

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...

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...