dorsal/arxiv
View SchemaCross-Market Alpha: Testing Short-Term Trading Factors in the U.S. Market via Double-Selection LASSO
| Authors | Jin Du, Alexander Walter, Maxim Ulrich |
|---|---|
| Categories | |
| ArXiv ID | 2601.06499vv1 |
| URL | https://arxiv.org/abs/2601.06499 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
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.
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"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.",
"arxiv_id": "2601.06499",
"authors": [
"Jin Du",
"Alexander Walter",
"Maxim Ulrich"
],
"categories": [
"q-fin.ST"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Cross-Market Alpha: Testing Short-Term Trading Factors in the U.S. Market via Double-Selection LASSO",
"url": "https://arxiv.org/abs/2601.06499",
"version": "v1"
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