DP14266 Taming the Factor Zoo: A Test of New Factors

Author(s): Gavin Feng, Stefano W Giglio, Dacheng Xiu
Publication Date: January 2020
Keyword(s): Elastic Net, Factors, Lasso, Machine Learning, PCA, Post-Selection Inference, Regularized Two-Pass Estimation, Stochastic discount factor, variable selection
JEL(s):
Programme Areas: Financial Economics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=14266

We propose a model selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high-dimensional set of existing factors explains. Our methodology accounts for model selection mistakes that produce a bias due to omitted variables, unlike standard approaches that assume perfect variable selection. We apply our procedure to a set of factors recently discovered in the literature. While most of these new factors are shown to be redundant relative to the existing factors, a few have statistically significant explanatory power beyond the hundreds of factors proposed in the past.