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...

We introduce artificial intelligence pricing theory (AIPT). In contrast with the APT's foundational assumption of a low dimensional factor structure in returns, the AIPT conjectures that returns are driven by a large number of factors. We first verify this conjecture empirically and show that...

Stock markets play a dual role: help allocate capital by conveying information about firms' fundamentals and provide liquidity by quickly turning stocks into cash. We propose a trading model in which these two roles are endogenously related: more intensive use of stocks for liquidity affects...

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...

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...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We characterize how risk evolves during a crisis. Using high-frequency data, we find that the first two principal components (PCs) of the covariance matrix of global asset returns experience large, sudden, and temporary spikes coinciding with well-known crises - Covid-19 pandemic, Global...

Studies of intermediated arbitrage argue that bank balance sheets are an important consideration, yet little evidence exists on banks' positioning in this context. Using confidential supervisory data (covering $25 trillion in daily notional exposures) we examine banks' positions in connection...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...

Is shareholder interest in corporate social responsibility driven by pecuniary motives (abnormal rates of return) or non-pecuniary ones (willingness to sacrifice returns to address various firm externalities)? To answer this question, we categorize the literature into seven tests: (1) costs of...