Selecting and Testing Asset Pricing Models: A Stepwise Approach

Guanhao Feng, Wei Lan, Hansheng Wang, Jun Zhang

    Research output: Working PapersPreprint

    Abstract

    The asset pricing literature emphasizes factor models that minimize pricing errors but overlooks unselected candidate factors that could enhance the performance of test assets. This paper proposes a framework for factor model selection and testing by (i) selecting the optimal model that spans the joint efficient frontier of test assets and all candidate factors, and (ii) testing pricing performance on both test assets and unselected candidate factors. Our framework updates a baseline model (e.g., CAPM) sequentially by adding or removing factors based on asset pricing tests. Ensuring model selection consistency, our framework utilizes the asset pricing duality: minimizing cross-sectionally unexplained pricing errors aligns with maximizing the Sharpe ratio of the selected factor model. Empirical evidence shows that workhorse factor models fail asset pricing tests, whereas our proposed 8-factor model is not rejected and exhibits robust out-of-sample performance.
    Original languageEnglish
    PublisherSocial Science Research Network (SSRN)
    Number of pages48
    DOIs
    Publication statusOnline published - 30 Jul 2023

    Bibliographical note

    Research Unit(s) information for this publication is provided by the author(s) concerned.

    Research Keywords

    • anomalies
    • factor efficiency
    • stepwise selection
    • GRS test
    • model comparison
    • Sharpe ratio

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