We are the first pioneers who evaluate the overall fitness of the two-pass Fama–MacBeth regression and the generalized method of moments (GMM) by comparing the R 2 or mean absolute pricing error (MAE), using a Monte Carlo simulation of different models and portfolios for hundreds of trials and, in particular, focusing on the case that the expected return is always a gross return in both methods. Our findings reveal an innovative finding that both methodologies achieve approximate overall magnitudes of pricing errors.