LLM-Based High-Growth Potential Ranking and Portfolio Selection: Evidence from China's Optical Industry
A 2026 paper by Lin and Xue on news sentiment and text signals in equities, using a large language model: the abstract mentions a Sharpe ratio, an information ratio, excess returns, profits and a benchmark and leaves out an out-of-sample test, transaction costs, multiple testing and the size of the universe.
“The results show that all LLM portfolios outperform the benchmark across the four performance measures, with portfolios formed from the highest-ranked stocks exhibiting the strongest performance.”
AssetEquities
StrategyNews sentimentportfolio optimization
TechniqueLarge language model
GeographyChina
Also stated: Sharpe ratio, Information ratio, Excess return, Profit, Text and news, benchmark
Missing from abstract: 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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