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Generalized Portfolio Sorts for Factor Validation

Author

Listed:
  • Markus Schmid

    (University of St. Gallen - Swiss Institute of Banking and Finance; University of St. Gallen - School of Finance; Swiss Finance Institute; European Corporate Governance Institute (ECGI))

  • Daniel Hoechle

    (FHNW School of Business - Institute for Finance; University of Basel - Department of Finance)

  • Heinz Zimmermann

    (University of Basel - Faculty of Business and Economics)

Abstract

Portfolio sorts are widely used in empirical asset pricing to identify firm characteristics that predict stock returns. However, such tests can conflate genuine characteristic-based predictability with persistent, firm-level heterogeneity. To address this limitation, we propose a Generalized Portfolio Sorts (GPS) model, which can exactly replicate results from all variants of conventional portfolio sorts, but can also be specified so that it separates a firm characteristic’s genuine predictive power from stable firm-level factors. We also derive a statistical test to detect whether return predictability arises from the sorting characteristic itself or from persistent, firm-level traits. Applied to a large set of proposed asset pricing predictors, we find that nearly half lose significance once persistent, firm-level heterogeneity is accounted for. The GPS-model thus strengthens factor validation, advances our understanding of the factor zoo, and provides a more robust foundation for empirical asset pricing tests.

Suggested Citation

  • Markus Schmid & Daniel Hoechle & Heinz Zimmermann, 2025. "Generalized Portfolio Sorts for Factor Validation," Swiss Finance Institute Research Paper Series 25-32, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp2532
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    More about this item

    Keywords

    Portfolio sorts; cross-section of expected returns; tests of asset pricing models; random effects assumption;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D1 - Microeconomics - - Household Behavior

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