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Working Paper
Machine Learning and the Implementable Efficient Frontier
August 18, 2022
We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading costs leads to excessive reliance on fleeting small-scale characteristics, resulting in poor net returns. We develop a framework that produces a superior frontier by integrating trading-cost-aware portfolio optimization with machine learning
Working Paper
Climate Finance
October 29, 2020
The paper reviews the literature studying interactions between climate change and financial markets, including various approaches to incorporating climate risk in macro-finance models as well as the empirical literature that explores the pricing of climate risks across several asset classes.
Working Paper
Understanding Momentum and Reversals
June 9, 2020
Stock momentum, long-term reversal, and other past return characteristics that predict future returns also predict future realized betas, suggesting these characteristics capture time-varying risk compensation.
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.
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.
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.