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

Thomas Wong, Mauricio Barahona
3/26/2023
q-fin.STcs.LG

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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.

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Cite this paper

@article{wong2023feature,
  title  = {Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions},
  author = {Thomas Wong and Mauricio Barahona},
  year   = {2023},
  eprint = {2303.16117},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.16117v2}
}

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