The New Quant: A Survey of Large Language Models in Financial Prediction and Trading
Fu (2025) studies news sentiment and text signals in equities using a large language model. The abstract does not mention a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“We review empirical evidence for predictability, highlight design patterns that improve faithfulness such as retrieval first prompting and tool-verified numerics, and explain how signals feed portfolio construction under exposure, turnover, and capacity controls.”
AssetEquities
StrategyNews sentimentportfolio optimization
TechniqueLarge language model
InputsText 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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