"Generating long-horizon stock ""buy"" signals with a neural language model"
News sentiment and text signals in equities, studied by Bock in 2024 with a large language model. The abstract mentions a benchmark and an out-of-sample test but not transaction costs, multiple testing or the size of the universe.
“As measured by the F1 score, the buy signal provides between 4.8 and 9 percent improvement against a random stock selection model.”
AssetEquitiesindices
StrategyNews sentimentmacro signals
TechniqueLarge language model
GeographyUS
Also stated: Annual, Text and news, benchmark, out-of-sample test
Missing from abstract: costs, multiple testing, universe
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The paper's neighbourhoodNews sentiment and text signals by year
FamilyNews sentiment and text signals148Momentum and trend following289Factor investing240Machine learning return prediction15318 more · 854
AssetEquities97
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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