Deep learning-based analysis of investor sentiment and stock return prediction: an experimental finance perspective
A 2026 paper by Zheng and co-authors on machine learning return prediction 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.
“Empirical results show that, after controlling for past market returns, changes in investor sentiment in the first half-hour predict the returns of the SSE Composite Index in the last half-hour.”
AssetEquities
StrategyMachine learningnews sentiment
TechniqueLarge language modelfeedforward network
FrequencyIntraday
Also stated: Macro, Text and news
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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The paper's neighbourhoodMachine learning return prediction by year
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