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Working Paper
Hedging Climate Change News
May 22, 2019
We propose and implement a procedure to dynamically hedge climate change risk and discuss multiple directions for future research on financial approaches to managing climate risk.
Working Paper
Autoencoder Asset Pricing Models
May 22, 2019
We propose a new latent factor conditional asset pricing model, which delivers out-of-sample pricing errors that are far smaller (and generally insignificant) compared to other leading factor models.
Working Paper
Predicting Returns with Text Data
December 19, 2019
We introduce a new text-mining methodology that extracts sentiment information from news articles to predict asset returns.
Working Paper
Forecasting the Distribution of Option Returns
December 12, 2018
We propose a method for constructing conditional option return distributions.
Working Paper
Characteristics Are Covariances: A Unified Model of Risk and Return
October 18, 2018
We propose a new modeling approach for the cross section of returns that helps determine whether excess returns to factors are driven by compensation for risk, or an anomaly effect.
Journal Article
Empirical Asset Pricing via Machine Learning
October 17, 2018
We show how the field of machine learning can be used to empirically investigate asset premia including momentum, liquidity, and volatility.
Working Paper
Credit Implied Volatility
March 10, 2015
This paper introduces the concept of a credit implied volatility surface. The credit implied volatility (CIV) can be interpretable as risk-neutral asset volatility of the underlying firm—the slope of the CIV term structure is negative in downturns and positive during expansions.
Journal Article
Factor Momentum Everywhere
January 29, 2019
Can individual factors be reliably timed based on their recent performance? This study of 65 widely-studied, characteristic-based equity factors aims to find out.
White Paper
Equity Term Structures without Dividend Strips Data
March 12, 2020
We use a large cross-section of equity returns to estimate a rich affine model of equity prices, dividends, returns and their dynamics.. The new term structure data generated by our model represent new empirical moments that can be used to guide and evaluate asset pricing models.
Working Paper
Principal Portfolios
July 7, 2020
We propose a new asset-pricing framework in which all securities’ signals are used to predict each individual return. While the literature focuses on each security’s own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictability.