A0566
Title: Test assets and weak factors
Authors: Stefano Giglio - Yale and NBER (United States) [presenting]
Dacheng Xiu - University of Chicago (United States)
Abstract: Weak factors, factors to which test assets are only weakly exposed, represent an important concern in empirical asset pricing. A novel methodology is proposed to address this issue, supervised PCA (SPCA). SPCA iterates a supervised asset selection step, in which only informative test assets are selected, and a principal-component estimation step to extract factors. It can be used to estimate risk premia and diagnose factor models even when weak factors are present and not all true factors are observed. SPCAs asymptotic properties are derived and several empirical applications of the methodology are illustrated.
