The historical returns on equity index options are well known to be strikingly negative. That is typically explained either by investors having convex marginal utility over stock returns (e.g. crash/variance aversion) or by intermediaries demanding a premium for hedging risk. This paper examines...

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...

This paper describes a process for automatically generating academic finance papers using large language models (LLMs). It demonstrates the process' efficacy by producing hundreds of complete papers on stock return predictability, a topic particularly well-suited for our illustration. We first...

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...

Between 2016 and 2023, the top 10% of carbon-emission-intensive firms (heavy emitters) accounted for over 90% of all Scope 1 emissions from U.S. public companies. We observe that about 35% of the market capitalization of 'Value' portfolios, compared to 5% of 'Growth' portfolios, regardless of...

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...