Corpus ID: 235125787

Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures

@article{Poh2021EnhancingCC,
  title={Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures},
  author={Daniel Poh and Bryan Lim and S. Zohren and Stephen J. Roberts},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.10019}
}
The performance of a cross-sectional currency strategy depends crucially on accurately ranking instruments prior to portfolio construction. While this ranking step is traditionally performed using heuristics, or by sorting outputs produced by pointwise regression or classification models, Learning to Rank algorithms have recently presented themselves as competitive and viable alternatives. Despite improving ranking accuracy on average however, these techniques do not account for the possibility… Expand

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