QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model
News sentiment and text signals, studied by Wang and co-authors in 2024 with 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.
“The core challenge involves efficiently building and integrating a domain-specific knowledge base for the agent's learning process.”
StrategyNews sentiment
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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