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Financial Machine Learning

Author

Listed:
  • Bryan Kelly
  • Dacheng Xiu
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.

Suggested Citation

  • Bryan Kelly & Dacheng Xiu, 2023. "Financial Machine Learning," Foundations and Trends(R) in Finance, now publishers, vol. 13(3-4), pages 205-363, November.
    • Handle: RePEc:now:fntfin:0500000064
    DOI: 10.1561/0500000064
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    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
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    5. JULES H. Van BINSBERGEN & RALPH S. J. KOIJEN, 2010. "Predictive Regressions: A Present‐Value Approach," Journal of Finance, American Finance Association, vol. 65(4), pages 1439-1471, August.
    6. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    7. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    8. Motohiro Yogo, 2006. "A Consumption‐Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.
    9. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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    Cited by:

    1. Göncü, Ahmet & Kuzubaş, Tolga U. & Saltoğlu, Burak, 2024. "Predicting oil prices: A comparative analysis of machine learning and image recognition algorithms for trend prediction," Finance Research Letters, Elsevier, vol. 67(PB).
    2. Ledoit, Olivier & Wolf, Michael, 2025. "Markowitz portfolios under transaction costs," The Quarterly Review of Economics and Finance, Elsevier, vol. 100(C).
    3. Huo, Da & Shi, Yongdong & Wang, Chao & Wang, Lihan & Xing, Weize & Yang, Mo & Zhao, Jingjing, 2025. "Measuring systemic risk in China: A new hybrid approach incorporating ensemble learning and risk spillover networks," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
    4. Zhao, Yuchen & Bi, Xiaogang & Ma, Qing-Ping, 2025. "Predicting mergers & acquisitions: A machine learning-based approach," International Review of Financial Analysis, Elsevier, vol. 99(C).

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