GMM weighting matrices in cross-sectional asset pricing tests

Nora Laurinaityte, Christoph Meinerding, Christian Schlag and Julian Thimme

Journal of Banking & Finance, 2024, vol. 162, issue C

Abstract: When estimating misspecified linear factor models for the cross-section of expected returns using GMM, the explanatory power of these models can be spuriously high when the estimated factor means are allowed to deviate substantially from the sample averages. In fact, by shifting the weights on the moment conditions, any level of cross-sectional fit can be attained. The mathematically correct global minimum of the GMM objective function can be obtained at a parameter vector that is far from the true parameters of the data-generating process. This property is not restricted to small samples, but rather holds in population. It is a feature of the GMM estimation design and applies to both strong and weak factors, as well as to all types of test assets.

Keywords: Asset pricing; Cross-section of expected returns (search for similar items in EconPapers)
JEL-codes: C13 C21 G00 G12 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:162:y:2024:i:c:s0378426624000438

DOI: 10.1016/j.jbankfin.2024.107123

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