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Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?

Author

Listed:
  • Huei-Wen Teng

    (National Yang Ming Chiao Tung University)

  • Yu-Hsien Li

    (Taishin International Bank)

Abstract

In asset pricing, most studies focus on finding new factors, such as macroeconomic factors or firm characteristics, to explain risk premiums. Investigating whether these factors help forecast stock returns remains active research in finance and computer science. This paper conducts an extensive comparative analysis using a large set of pricing factors. It compares out-of-sample stock-level and portfolio-level prediction performance among neural networks, the traditional Fama-MacBeth regression, and other supervised learning algorithms such as regression and tree-based algorithms. Our analysis shows the benefit of employing neural networks, and deeper neural networks enjoy marginal improvements in terms of prediction.

Suggested Citation

  • Huei-Wen Teng & Yu-Hsien Li, 2023. "Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?," Digital Finance, Springer, vol. 5(1), pages 149-182, March.
  • Handle: RePEc:spr:digfin:v:5:y:2023:i:1:d:10.1007_s42521-023-00076-y
    DOI: 10.1007/s42521-023-00076-y
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    References listed on IDEAS

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    More about this item

    Keywords

    Asset pricing; Fama-MacBeth regression; Elastic net; Regression tree; Boosting; Neural network;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions

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