Factor Models, Machine Learning, and Asset Pricing
35 Pages Posted: 18 Oct 2021 Last revised: 18 Feb 2022
Date Written: October 15, 2021
We survey recent methodological contributions in asset pricing using factor models and machine learning. We organize these results based on their primary objectives: estimating expected returns, factors, risk exposures, risk premia, and the stochastic discount factor, as well as model comparison and alpha testing. We also discuss a variety of asymptotic schemes for inference. Our survey is a guide for financial economists interested in harnessing modern tools with rigor, robustness, and power to make new asset pricing discoveries, and it highlights directions for future research and methodological advances.
Keywords: asset pricing, machine learning, factor models, stochastic discount factor, risk premium
JEL Classification: G1, G14, C10, C38, C45, C55, C58
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