← Search

Review of Finance Vol. 22 No. 2 2018

Linear Approximations and Tests of Conditional Pricing Models

Michael W. Brandt1; David A. Chapman2

1 Duke University · 2 University of Virginia

Abstract

If a nonlinear risk premium in a conditional asset pricing model is approximated with a linear function, as is commonly done in empirical research, the fitted model is misspecified. We use a generic reduced-form model economy with moderate risk premium nonlinearity to examine the size of the resulting misspecification-induced pricing errors. Pricing errors from moderate nonlinearity can be large, and a version of a test for nonlinearity based on risk premiums rather than pricing errors has reasonable power properties after properly controlling for the size of the test. We conclude by examining the importance of moderate nonlinearity in the context of the investment-specific technology shock models of Papanikolaou (2011) and Kogan and Papanikolaou (2014).

DOI
10.1093/rof/rfy003
Volume
22
Issue
2
Pages
455-489
Language
en
Sources
bibtex:phds-export.bib openalex crossref

Cite