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Financial Machine Learning

Bryan Kelly & Dacheng Xiu

Foundations and Trends in Finance2023https://doi.org/10.1561/0500000064article
AJG 2ABDC B
Weight
0.75

Abstract

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping machine learning tools, as well as for statisticians and machine learners seeking interesting financial contexts where advanced methods may be deployed.

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https://doi.org/https://doi.org/10.1561/0500000064

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@article{bryan2023,
  title        = {{Financial Machine Learning}},
  author       = {Bryan Kelly & Dacheng Xiu},
  journal      = {Foundations and Trends in Finance},
  year         = {2023},
  doi          = {https://doi.org/https://doi.org/10.1561/0500000064},
}

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Financial Machine Learning

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Evidence weight

0.75

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact1.00 × 0.4 = 0.40
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.