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Misspecification-Robust Inference in Linear Asset-Pricing Models with Irrelevant Risk Factors

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Listed:
  • Nikolay Gospodinov
  • Raymond Kan
  • Cesare Robotti

Abstract

This paper shows that in misspecified models with risk factors that are uncorrelated with the test asset returns, the conventional inference methods tend to erroneously conclude, with high probability, that these factors are priced. Our proposed model selection procedure, which is robust to identification failure 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. Applying our methodology to several popular asset-pricing models suggests that only the market and book-to-market factors appear to be priced, while the statistical evidence on the pricing ability of many macroeconomic factors is rather weak.

Suggested Citation

  • Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2014. "Misspecification-Robust Inference in Linear Asset-Pricing Models with Irrelevant Risk Factors," The Review of Financial Studies, Society for Financial Studies, vol. 27(7), pages 2139-2170.
    • Handle: RePEc:oup:rfinst:v:27:y:2014:i:7:p:2139-2170.
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    File URL: http://hdl.handle.net/10.1093/rfs/hht135
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    References listed on IDEAS

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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

    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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