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Misspecification-robust inference in linear asset pricing models with irrelevant risk factors

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Abstract

We show that in misspecified models with useless factors (for example, factors that are independent of the returns on the test assets), the standard inference procedures tend to erroneously conclude, with high probability, that these irrelevant factors are priced and the restrictions of the model hold. Our proposed model selection procedure, which is robust to useless factors and potential model misspecification, restores the standard inference and proves to be effective in eliminating factors that do not improve the model's pricing ability. The practical relevance of our analysis is illustrated using simulations and empirical applications.

Suggested Citation

  • Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2013. "Misspecification-robust inference in linear asset pricing models with irrelevant risk factors," FRB Atlanta Working Paper 2013-09, Federal Reserve Bank of Atlanta.
    • Handle: RePEc:fip:fedawp:2013-09
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    1. Kan, Raymond & Robotti, Cesare, 2008. "Specification tests of asset pricing models using excess returns," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 816-838, December.
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    More about this item

    Keywords

    asset pricing models; lack of identification; model misspecification; GMM estimation;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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