The Macroeconomy and the Cross-Section of International Equity Index Returns: A Machine Learning Approach
Machine learning return prediction in equities, studied by Popescu in 2019 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.
“I find that macroeconomic signals seem to substantially improve out-of-sample performance, especially when non-linear features are incorporated via neural networks.”
AssetEquitiesindices, single stocks
StrategyMachine learningmacro signals
TechniqueFeedforward network
GeographyGlobal
Also stated: Long-short, Fundamentals, 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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