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Working Paper

Empirical Asset Pricing via Machine Learning

We show how the field of machine learning can be used to empirically investigate asset premia including momentum, liquidity, and volatility.

Working Paper

Hedging Climate Change News

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.

Journal Article

A Data Science Solution to the Multiple-Testing Crisis in Financial Research

In this paper, we present a real example of how multiple testing information can be reported. We use that information to estimate the Deflated Sharpe Ratio of an investment strategy.

Alternative Thinking

Can Machines "Learn" Finance?

The early evidence hints that machine learning tools can potentially improve investment portfolios. Application of machine learning techniques is a natural evolution for investment research, and one that will continue to be explored.

Working Paper

Autoencoder Asset Pricing Models

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.