Cross-sectional tests of multifactor CCAPMs using conditional moments and time-series restrictions

Two different methods are used to evaluate the performance of the consumption-based asset pricing models to explain the cross-section of expected stock returns in conditional moments: one is to scale the returns, and the other is to model time-varying factor loadings, using instrument variables. Maximum correlation portfolios are constructed to directly impose restrictions on the time-series intercepts, especially in a model whose factors are not returns. The empirical results are as follow: the consumption-based models perform no better than the standard CAPM; adding the return on human capital as an additional risk factor does not help explain the cross-section; and the Fama- French three-factor model shows the best ability to lower the pricing error.