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Statistical Inferences with Model Selection Criteria

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Abstract

Deficiency in the empirical applications of asset pricing models leads research toward some model selection criteria to justify the search. Unfortunately, with criteria that either emphasize the forecastability of models or impose a penalty for the increase of dimensionality (or complexity), the search for empirical asset pricing models tends to ignore the necessary role of the identified variables or factors to portrait the systematic and intrinsic commonality for all asset returns. That is to say, the coherence or strength of this systematic and intrinsic commonality in asset returns should be emphasized—in addition to the dimensionality and complexity. (Asymptotic) non-diversifiability, for instance, is an obvious requirement. In addition, almost all of this field of research into model selection of asset returns assumes that there exists a “true” (or correct) factor-pricing model in the data generating mechanism. Although robustness in asymptotic arguments are all provided in these studies, little discussion is provided for the soundness of such an assumption.

Keywords

Model Selection Criteria Empirical Asset Pricing Models Asset Returns Intrinsic Commonality Approximate Factor Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2018

Authors and Affiliations

  1. 1.School of Business and ManagementAzusa Pacific UniversityStevenson RanchUSA

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