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Interacting Anomalies

Karsten Müller & Simon Schmickler

Review of Asset Pricing Studies2025https://doi.org/10.1093/rapstu/raaf001article
AJG 3ABDC A*
Weight
0.50

Abstract

An extensive literature studies interactions of stock market anomalies using double-sorted portfolios. But given hundreds of known candidate anomalies, examining selected interactions is subject to a data mining critique. In this paper, we conduct a comprehensive analysis of all possible double-sorted portfolios constructed from 102 underlying anomalies. We find hundreds of statistically significant anomaly interactions, even after accounting for multiple hypothesis testing. An out-of-sample trading strategy that invests in the top backward-looking double-sort strategy generates equal-weighted (value-weighted) monthly average returns of 4% (2.7%) at an annualized Sharpe ratio of 2 (1.38), on par with state-of-the-art anomaly-based machine learning strategies.

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https://doi.org/https://doi.org/10.1093/rapstu/raaf001

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@article{karsten2025,
  title        = {{Interacting Anomalies}},
  author       = {Karsten Müller & Simon Schmickler},
  journal      = {Review of Asset Pricing Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1093/rapstu/raaf001},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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