Testing Factor Models in the Cross-Section

Abstract

The standard full-sample time-series asset pricing test suffers from poor statistical properties, lookahead bias, constant-beta assumptions, and rejects models when average factor returns deviate from risk premia. We therefore confront prominent equity pricing models with the classical Fama and MacBeth (1973) cross-sectional test. For all models, we uncover three main findings: (i) the intercept coefficients are economically large and highly statistically significant; (ii) cross-sectional factor risk premium estimates are generally far below the average factor excess returns; and (iii) they are usually not statistically significant. Overall, all new factor models are inconsistent with no-arbitrage pricing and cannot accurately explain the cross-section of stock returns.