MGPraxis6,400 papers identified by name

Incorporating Price Limits into Deep Learning for Stock Return Prediction in the Chinese A-Share Market

张璠 Zhang Fan, Haobing Wang·2026
SSRN 6941698 ↗

A 2026 paper by Fan and Wang on machine learning return prediction in equities, using a transformer on a 2019–2026 sample: the abstract does not mention a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.

“The Student-t Tobit loss improves cross-sectional ranking performance over the MSE baseline in three out of four architectures, with the largest gain for MLP (Rank IC from 0.0390 to 0.0666), driven primarily by better performance on non-limit observations.”

AssetEquities
StrategyMachine learning
TechniqueTransformerrecurrent neural network
GeographyChina

Also stated: Daily, 2019–2026

Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe

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The paper's neighbourhoodMachine learning return prediction by year
■ equities■ crypto■ commodities■ bonds and credit■ other assets2010201520201862This paper2026■ equities■ crypto■ commodities■ bonds and credit■ other assets20102015202062This paper2026
FamilyMachine learning return prediction153Momentum and trend following289Factor investing240News sentiment and text signals14818 more · 854
AssetEquities106Crypto11
MethodNeural networks88Linear factor models26Tree ensembles26Language models184 more · 14
AuthorsFan, Wang2Bryan T. Kelly4Turan G. Bali3David E. Rapach31 more · 3
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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