Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/101040 
Erscheinungsjahr: 
2013
Schriftenreihe/Nr.: 
Working Paper No. 2013-9
Verlag: 
Federal Reserve Bank of Atlanta, Atlanta, GA
Zusammenfassung: 
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.
Schlagwörter: 
asset pricing models
lack of identification
model misspecification
GMM estimation
JEL: 
G12
C12
C52
Dokumentart: 
Working Paper

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