Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions
Statistical Finance
2023-04-19 v2 Machine Learning
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.
Keywords
Cite
@article{arxiv.2303.16117,
title = {Feature Engineering Methods on Multivariate Time-Series Data for Financial Data Science Competitions},
author = {Thomas Wong and Mauricio Barahona},
journal= {arXiv preprint arXiv:2303.16117},
year = {2023}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2303.07925