Feature Learning for Stock Price Prediction Shows a Significant Role of Analyst Rating
A 2021 paper by Singh and Khushi on machine learning return prediction in equities: the abstract mentions excess returns and a benchmark and leaves out an out-of-sample test, transaction costs, multiple testing and the size of the universe.
“From any given day, we were able to predict the direction of change in price by 1% up to 10 days in the future.”
AssetEquitiesindices
StrategyMachine learning
GeographyUS
ClaimExcess return
Also stated: Price and volume, Fundamentals, benchmark
Missing from abstract: 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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