We perform a comparative analysis of machine learning methods for the canonical problem
of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic …

An ever-increasing share of human interaction, communication, and culture is recorded as
digital text. We provide an introduction to the use of text as an input to economic research. We …

We empirically analyze the pricing of political uncertainty, guided by a theoretical model of
government policy choice. To isolate political uncertainty, we exploit its variation around …

We propose a new modeling approach for the cross section of returns. Our method,
Instrumented Principal Component Analysis (IPCA), allows for latent factors and time-varying …

We propose a new measure of time-varying tail risk that is directly estimable from the cross-section
of returns. We exploit firm-level price crashes every month to identify common …

We find that shocks to the equity capital ratio of financial intermediaries—Primary Dealer
counterparties of the New York Federal Reserve—possess significant explanatory power for …

We provide evidence for the importance of information asymmetry in asset pricing by using
three natural experiments. Consistent with rational expectations models with multiple assets …

A new covariance matrix estimator is proposed under the assumption that at every time
period all pairwise correlations are equal. This assumption, which is pragmatically applied in …

We show that firms׳ idiosyncratic volatility obeys a strong factor structure and that shocks to
the common idiosyncratic volatility (CIV) factor are priced. Stocks in the lowest CIV-beta …

Objectives: The purpose of this study was to determine what factors influence the maintenance
of fracture reduction after locked plating of proximal humerus fractures, and particularly …