Factor Investing Lecture 9: Machine Learning in Factor Investing (Presentation Slides)
Factor investing in equities, studied by Shi in 2025 with a feedforward neural network. The abstract mentions transaction costs but not a benchmark, an out-of-sample test, multiple testing or the size of the universe.
“The notes critically examine common misconceptions about machine learning in finance, emphasizing the importance of integrating financial theory, model interpretability, and realistic expectations for performance improvements.”
AssetEquities
StrategyFactor investing
TechniqueFeedforward network
GeographyChina
Also stated: costs
Missing from abstract: benchmark, out-of-sample test, 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.
| Similar papers | citation | same method | same asset | same authors | |
|---|---|---|---|---|---|
| A Deep Multi-Factor Framework for Cross-Sectional Stock Return Ranking via Market-State Attention Pooling by Wu and Liu | 2026 | ||||
| Multifactor Timing with Deep Learning by Cotturo et al. | 2026 | ||||
| Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks by Lai | 2026 | ||||
| Deep Learning for Short Term Equity Trend Forecasting: A Behavior Driven Multi Factor Approach by Luan | 2025 | ||||
| Multi-Factor Timing with Deep Learning by Cotturo et al. | 2024 |