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Recovering Missing Firm Characteristics with Attention-Based Machine Learning

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  • Beckmeyer, Heiner
  • Wiedemann, Timo

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  • Beckmeyer, Heiner & Wiedemann, Timo, 2022. "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics 264135, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc22:264135
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    File URL: https://www.econstor.eu/bitstream/10419/264135/1/vfs-2022-pid-70665.pdf
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    References listed on IDEAS

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    4. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
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    6. Jason Abrevaya & Stephen G. Donald, 2017. "A GMM Approach for Dealing with Missing Data on Regressors," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 657-662, July.
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    11. Gu, Shihao & Kelly, Bryan & Xiu, Dacheng, 2021. "Autoencoder asset pricing models," Journal of Econometrics, Elsevier, vol. 222(1), pages 429-450.
    12. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
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    17. Andrew Y. Chen & Tom Zimmermann, 2022. "Open Source Cross-Sectional Asset Pricing," Critical Finance Review, now publishers, vol. 11(2), pages 207-264, May.
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    Cited by:

    1. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
    2. Junyi Ye & Bhaskar Goswami & Jingyi Gu & Ajim Uddin & Guiling Wang, 2024. "From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing," Papers 2403.06779, arXiv.org.

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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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