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GMM weighting matrices incross-sectional asset pricing tests

Author

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  • Laurinaityte, Nora
  • Meinerding, Christoph
  • Schlag, Christian
  • Thimme, Julian

Abstract

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.

Suggested Citation

  • Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:622020
    as

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    References listed on IDEAS

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    More about this item

    Keywords

    asset pricing; cross-section of expected returns; GMM; factor zoo;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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