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Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions

Author

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  • Thomas Wong
  • Mauricio Barahona

Abstract

This paper is a work in progress. We are looking for collaborators to provide us financial datasets in Equity/Futures market to conduct more bench-marking studies. The authors have papers employing similar methods applied on the Numerai dataset, which is freely available but obfuscated. We apply different feature engineering methods for time-series to US market price data. The predictive power of models are tested against Numerai-Signals targets.

Suggested Citation

  • Thomas Wong & Mauricio Barahona, 2023. "Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions," Papers 2303.16117, arXiv.org, revised Apr 2023.
    • Handle: RePEc:arx:papers:2303.16117
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    File URL: http://arxiv.org/pdf/2303.16117
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