Information Diffusion and Return Predictability across Business and Ownership Networks: Evidence from Korea
A 2026 paper by Lee and Lim on machine learning return prediction, 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.
“Lagged peer returns from both layers predict focal-firm returns and generate positive risk-adjusted portfolio returns.”
StrategyMachine learning
TechniqueLarge language modellinear factor model
GeographyEmerging markets
FrequencyAnnual
Also stated: 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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