Identification of Factor Risk Premia

35 Pages Posted: 5 Oct 2021

See all articles by Peter Hansen

Peter Hansen

Mitchell E. Daniels, Jr School of Business, Purdue University

Maziar Kazemi

Arizona State University (ASU) - Finance Department

Date Written: October 1, 2021

Abstract

This paper a develops novel statistical test of whether individual factor risk premia are identified from return data in multi-factor models. We give a necessary and sufficient condition for population identification of individual risk premia, which we call the kernel-orthogonality condition. This condition is weaker than the standard rank condition commonly assumed for linear factor models. Under misspecification, our condition ensures point identification of the risk premium with minimal pricing error. We show how to test this restriction directly in reduced-rank models. Finally, we apply our test methodology to assess identification of risk premia associated with consumption growth and intermediary leverage.

Keywords: Linear factor models, Underidentification test, Risk premia

JEL Classification: G12, C12, C58

Suggested Citation

Hansen, Peter and Kazemi, Maziar, Identification of Factor Risk Premia (October 1, 2021). Available at SSRN: https://ssrn.com/abstract=3934624 or http://dx.doi.org/10.2139/ssrn.3934624

Peter Hansen (Contact Author)

Mitchell E. Daniels, Jr School of Business, Purdue University ( email )

403 Mitch Daniels Blvd.
West Lafayette, IN 47907
United States

Maziar Kazemi

Arizona State University (ASU) - Finance Department ( email )

W. P. Carey School of Business
PO Box 873906
Tempe, AZ 85287-3906
United States

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