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Cross-Market Alpha: Testing Short-Term Trading Factors in the U.S. Market via Double-Selection LASSO

Author

Listed:
  • Jin Du
  • Alexander Walter
  • Maxim Ulrich

Abstract

Current asset pricing research exhibits a significant gap: a lack of sufficient cross-market validation regarding short-term trading-based factors. Against this backdrop, the development of the Chinese A-share market which is characterized by its retail-investor dominance, policy sensitivity, and high-frequency active trading -- has given rise to specific short-term trading-based factors. This study systematically examines the universality of factors from the Alpha191 library in the U.S. market, addressing the challenge of high-dimensional factor screening through the double-selection LASSO algorithm an established method for cross-market, high-dimensional research. After controlling for 151 fundamental factors from the U.S. equity factor zoo, 17 Alpha191 factors selected by this procedure exhibit significant incremental explanatory power for the cross-section of U.S. stock returns at the 5% level. Together these findings demonstrate that short-term trading-based factors, originating from the unique structure of the Chinese A-share market, provide incremental information not captured by existing mainstream pricing models, thereby enhancing the explanation of cross-sectional return differences.

Suggested Citation

  • Jin Du & Alexander Walter & Maxim Ulrich, 2026. "Cross-Market Alpha: Testing Short-Term Trading Factors in the U.S. Market via Double-Selection LASSO," Papers 2601.06499, arXiv.org.
    • Handle: RePEc:arx:papers:2601.06499
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