Test Assets and Weak Factors

110 Pages Posted: 20 Jan 2021 Last revised: 23 Jun 2022

See all articles by Stefano Giglio

Stefano Giglio

Yale School of Management; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Dacheng Xiu

University of Chicago - Booth School of Business

Dake Zhang

University of Chicago - Booth School of Business

Multiple version iconThere are 4 versions of this paper

Date Written: January 17, 2021

Abstract

Weak factors – factors to which test assets are only weakly exposed – represent an important concern in empirical asset pricing. We propose a novel methodology 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. We derive SPCA’s asymptotic properties and illustrate several empirical applications of our methodology.

Keywords: Supervised PCA, SPCA, PCA, risk premium, factor models, APT, Ridge, Lasso, stochastic discount factor

Suggested Citation

Giglio, Stefano and Xiu, Dacheng and Zhang, Dake, Test Assets and Weak Factors (January 17, 2021). Chicago Booth Research Paper 21-04, Available at SSRN: https://ssrn.com/abstract=3768081 or http://dx.doi.org/10.2139/ssrn.3768081

Stefano Giglio (Contact Author)

Yale School of Management ( email )

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National Bureau of Economic Research (NBER) ( email )

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Centre for Economic Policy Research (CEPR) ( email )

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Dacheng Xiu

University of Chicago - Booth School of Business ( email )

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Chicago, IL 60637
United States

Dake Zhang

University of Chicago - Booth School of Business ( email )

5807 S Woodlawn Ave
Chicago, IL 60637
United States

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