Dirichlet policies for reinforced factor portfolios
Factor investing in equities, studied by André and Coqueret in 2021 with reinforcement learning. The abstract mentions a benchmark but not an out-of-sample test, transaction costs, multiple testing or the size of the universe.
“Across a large range of parametric choices, our result indicates that RL-based portfolios are very close to the equally-weighted (1/N) allocation.”
AssetEquities
StrategyFactor investing
TechniqueReinforcement learninglinear factor model
GeographyUS
Also stated: benchmark
Missing from abstract: 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
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|---|---|---|---|---|---|
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