Empirical Asset Pricing via Machine Learning
Machine learning return prediction in equities, studied by Gu, Kelly and Xiu in 2018 with a feedforward neural network. The abstract mentions an out-of-sample test but not a benchmark, transaction costs, multiple testing or the size of the universe.
“At the broadest level, we find that machine learning offers an improved description of expected return behavior relative to traditional forecasting methods.”
AssetEquities
StrategyMachine learningmomentum
TechniqueFeedforward networktree ensemble
Also stated: out-of-sample test
Missing from abstract: benchmark, costs, multiple testing, universe
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The paper's neighbourhoodMachine learning return prediction by year
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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