Misspecification-robust inference in linear asset pricing models with irrelevant risk factors
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.
|Date of creation:||01 Oct 2013|
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- Raymond Kan & Cesare Robotti, 2006.
"Specification tests of asset pricing models using excess returns,"
2006-10, Federal Reserve Bank of Atlanta.
- 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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