A Machine Learning Approach to Risk Factors: A Case Study Using the Fama–French–Carhart Model
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- Article
- Abstract
- BASIC FEATURES OF FACTOR MODELS
- MACHINE LEARNING AND THE RANDOM FOREST ALGORITHM
- BUILDING FACTOR MODELS USING RANDOM FORESTS
- USING FEATURE IMPORTANCES TO DERIVE PSEUDO-BETAS
- TRADING APPLICATION: BUILDING A SECTOR ROTATION STRATEGY USING THE RF FFC MODEL AND ASSOCIATION RULE LEARNING
- CONCLUSION
- ENDNOTES
- REFERENCES
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