GMM weighting matrices incross-sectional asset pricing tests

Cross-sectional asset pricing tests with GMM can generate spuriouslyhigh explanatory power for factor models when the moment conditions are specifiedsuch that they allow the estimated factor means to substantially deviate from theobserved sample averages. In fact, by shifting the weights on the moment conditions,any level of cross-sectional fit can be attained. This property is a feature of the GMMestimation design and applies to strong as well as weak factors, and to all samplesizes and test assets. We reveal the origins of this bias theoretically, gauge its sizeusing simulations, and document its relevance empirically.