Factor Investing with a Deep Multi-Factor Model
Wei, Dai and Lin (2022) study factor investing in equities using a feedforward neural network. The abstract mentions excess returns but not a benchmark, an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“Modeling and characterizing multiple factors is perhaps the most important step in achieving excess returns over market benchmarks.”
AssetEquities
StrategyFactor investing
TechniqueFeedforward networkgraph neural network
ClaimExcess return
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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The paper's neighbourhoodFactor investing by year
FamilyFactor investing240Momentum and trend following289Machine learning return prediction153News sentiment and text signals14818 more · 854
AssetEquities196
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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