Fine-Tuning Large Language Models for Stock Return Prediction Using Newsflow
“Among the three LLMs studied (DeBERTa, Mistral, Llama), Mistral performs more robustly across different universes; (3) return predictions derived from LLMs' text representations are a strong signal for portfolio construction, outperforming conventional sentiment scores.”
AssetEquities
StrategyNews sentimentmachine learning
TechniqueLarge language model
ClaimExcess return
Also stated: Long-short, Long-only, Fundamentals, Text and news
Missing from abstract: benchmark, out-of-sample test, 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
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