Shrinking the Cross Section

58 Pages Posted: 6 Dec 2017 Last revised: 12 Dec 2017

See all articles by Serhiy Kozak

Serhiy Kozak

University of Maryland - Robert H. Smith School of Business

Stefan Nagel

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER); Centre for Economic Policy Research; CESifo (Center for Economic Studies and Ifo Institute)

Shrihari Santosh

University of Maryland

Multiple version iconThere are 4 versions of this paper

Date Written: November 2017

Abstract

We construct a robust stochastic discount factor (SDF) that summarizes the joint explanatory power of a large number of cross-sectional stock return predictors. Our method achieves robust out-of-sample performance in this high-dimensional setting by imposing an economically motivated prior on SDF coefficients that shrinks the contributions of low-variance principal components of the candidate factors. While empirical asset pricing research has focused on SDFs with a small number of characteristics-based factors—e.g., the four- or five-factor models discussed in the recent literature—we find that such a characteristics-sparse SDF cannot adequately summarize the cross-section of expected stock returns. However, a relatively small number of principal components of the universe of potential characteristics-based factors can approximate the SDF quite well.

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Suggested Citation

Kozak, Serhiy and Nagel, Stefan and Santosh, Shrihari, Shrinking the Cross Section (November 2017). NBER Working Paper No. w24070. Available at SSRN: https://ssrn.com/abstract=3082232

Serhiy Kozak (Contact Author)

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Stefan Nagel

University of Chicago - Booth School of Business ( email )

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National Bureau of Economic Research (NBER)

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Centre for Economic Policy Research ( email )

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CESifo (Center for Economic Studies and Ifo Institute) ( email )

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Shrihari Santosh

University of Maryland ( email )

College Park
College Park, MD 20742
United States

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