The past half-century has seen major shifts in inflation expectations, how inflation comoves with the business cycle, and how stocks comove with Treasury bonds. Against this backdrop, we review the economic channels and empirical evidence on how inflation is priced in financial markets. Not all...

We treat expenditures that create intangible assets as investments and instead of expensing them, we add them back to earnings when measuring the return on equity of firms while constructing the profitability factor in the Fama and French (2015) five factor model. The profitability factor we...

We introduce FDIF, a measure of Fed communication surprise based on the text of FOMC statements. FDIF measures the difference between text-implied and actual values of key market variables. Positive FDIF of countercyclical variables (e.g., credit spreads) is associated with negative...

Using a two-period model of a commodity market with a large number of atomistic consumers and two strategic sellers, we show that a speculator with access to storage can lower the market price while buying and raise the price while selling by clever use of limit, stop-loss, and market orders....

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...

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 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...

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...

We measure the nature and severity of a variety of belief distortions in market reactions to hundreds of economic news events using a new methodology that synthesizes estimation of a structural asset pricing model with algorithmic machine learning to quantify bias. We estimate that investors...