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Factor Models, Machine Learning, and Asset Pricing

Stefano GiglioBryan T. KellyDacheng Xiu

出版	SSRN, 2022
URL	http://books.google.com.hk/books?id=1YbbzwEACAAJ&hl=&source=gbs_api

註釋

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.