Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions
“Results show that decoder-only language models outperform encoder baselines and dictionary sentiment in classification, calibration, return prediction, and net portfolio performance, while operational diagnostics reveal trade-offs among accuracy, latency, memory, throughput, and inference cost.”
AssetEquities
StrategyNews sentimentmachine learning
GeographyUS
ClaimExcess return
Also stated: Text and news, out-of-sample test, costs
Missing from abstract: benchmark, 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
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