98 Pages Posted: 22 Nov 2014
Date Written: January 15, 2018
We propose a new method to select amongst a large group of candidate factors -
many of which might arise as a result of data mining | that purport to explain the
cross-section of expected returns. The method is robust to general distributional characteristics
of both factor and asset returns. We allow for the possibility of time-series
as well as cross-sectional dependence. The technique accommodates a wide range of
test statistics. Our method can be applied to both asset pricing tests based on portfolio
sorts as well as tests using individual asset returns. In contrast to recent asset pricing
research, our study of individual stocks nds that the original market factor is by far
the most important factor in explaining the cross-section of expected returns.
Notes: This paper was formerly circulated under the title "How Many Factors?"
Keywords: Factors, Variable selection, Bootstrap, Data mining, Orthogonalization, Multiple testing, Predictive regressions, Fama-MacBeth, GRS, Performance evaluation, Return prediction
JEL Classification: G12, G14, C12, C21, C22, C31, C32
Suggested Citation: Suggested Citation