Linear Approximations and Tests of Conditional Pricing Models. (27th January 2018)

• Record Type: Journal Article
• Authors: Brandt, Michael W; Chapman, David A
• Is Part Of: Review of finance. Volume 22:Number 2(2018)
• Page Start: 455
• Page End: 489
• Publication Date: 2018-01-27
• Subjects: C58 -- G12; Conditional asset pricing model -- Nonlinear risk premiums -- Testing; Finance -- Europe -- Periodicals; Financiën; Finance; Periodicals; 332.09405
• DOI: 10.1093/rof/rfy003
• Languages: English
• ISSNs: 1572-3097

Abstract

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) .