TY  - JOUR
AU  - Kan,Raymond
AU  - Robotti,Cesare
AU  - Shanken,Jay
TI  - Pricing Model Performance and the Two-Pass Cross-Sectional Regression Methodology
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 15047
PY  - 2009
Y2  - June 2009
UR  - http://www.nber.org/papers/w15047
L1  - http://www.nber.org/papers/w15047.pdf
N1  - Author contact info:
Raymond Kan
University of Toronto
105 St. George Street
Toronto, Ontario
Canada M5S 3E6
E-Mail: kan@chass.utoronto.ca

Cesare Robotti
Federal Reserve Bank of Atlanta
Research Department
1000 Peachtree Street N.E.
Atlanta, Georgia 30309-4470
E-Mail: CRobotti@frbatlanta.org

Jay A. Shanken
Goizueta Business School
Emory University
1300 Clifton Road
Atlanta, GA 30322
Tel: 404/727-4772
Fax: 404/727-5238
E-Mail: jay_shanken@bus.emory.edu
AB  - Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular approach for estimating and testing asset pricing models. Statistical inference with this method is typically conducted under the assumption that the models are correctly specified, i.e., expected returns are exactly linear in asset betas. This can be a problem in practice since all models are, at best, approximations of reality and are likely to be subject to a certain degree of misspecification. We propose a general methodology for computing misspecification-robust asymptotic standard errors of the risk premia estimates. We also derive the asymptotic distribution of the sample CSR R2 and develop a test of whether two competing beta pricing models have the same population R2. This provides a formal alternative to the common heuristic of simply comparing the R2 estimates in evaluating relative model performance. Finally, we provide an empirical application which demonstrates the importance of our new results when applied to a variety of asset pricing models.
ER  -