TY  - JOUR
AU  - Brandt,Michael W.
AU  - Chapman,David A.
TI  - Linear Approximations and Tests of Conditional Pricing Models
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 12513
PY  - 2006
Y2  - September 2006
UR  - http://www.nber.org/papers/w12513
L1  - http://www.nber.org/papers/w12513.pdf
N1  - Author contact info:
Michael W. Brandt
Fuqua School of Business
Duke University
One Towerview Drive
Durham, NC  27708
Tel: 919/660-1948
Fax: 919/660-8038
E-Mail: mbrandt@duke.edu

David Chapman
Finance Dept.
Boston College
140 Comm. Ave., Fulton Hall 330
Chestnut Hill, MA 02467
E-Mail: david.chapman@bc.edu
AB  - We construct a simple reduced-form example of a conditional pricing model with modest intrinsic nonlinearity. The theoretical magnitude of the pricing errors (alphas) induced by the application of standard linear conditioning are derived as a direct consequence of an omitted variables bias. When the model is calibrated to either characteristics sorted or industry portfolios, we find that the alphas generated by approximation-induced specification error are economically large. A Monte Carlo analysis shows that finite-sample alphas are even larger. It also shows that the power to detect omitted nonlinear factors through tests based on estimated risk premiums can sometimes be quite low, even when the effect of misspecification on alphas is large.
ER  -