Linear approximations and tests of conditional pricing models

Published

Journal Article

© The Author(s) 2018. 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).

Full Text

Duke Authors

Cited Authors

  • Brandt, MW; Chapman, DA

Published Date

  • March 1, 2018

Published In

Volume / Issue

  • 22 / 2

Start / End Page

  • 455 - 489

Electronic International Standard Serial Number (EISSN)

  • 1573-692X

International Standard Serial Number (ISSN)

  • 1572-3097

Digital Object Identifier (DOI)

  • 10.1093/rof/rfy003

Citation Source

  • Scopus