Evaluating LLMs in Financial Tasks - Code Generation in Trading Strategies
A 2024 paper by Alonso and Dupouy on news sentiment and text signals, 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.
“The findings indicate that GPT-4-Turbo, Codellama-70B, and Gemini-Pro yield encouraging results relative to baseline computations, with GPT-4-Turbo achieving identical implementations to the baseline in certain instances.”
StrategyNews sentiment
TechniqueLarge language model
InputsPrice and volumetext 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
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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