• Corpus ID: 245218798

Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture

@article{Wood2021TradingWT,
  title={Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture},
  author={Kieran Wood and Sven Giegerich and Stephen J. Roberts and Stefan Zohren},
  journal={ArXiv},
  year={2021},
  volume={abs/2112.08534}
}
Deep learning architectures, specifically Deep Momentum Networks (DMNs) [1904.04912], have been found to be an effective approach to momentum and mean-reversion trading. However, some of the key challenges in recent years involve learning long-term dependencies, degradation of performance when considering returns net of transaction costs and adapting to new market regimes, notably during the SARS-CoV-2 crisis. Attention mechanisms, or Transformer-based architectures, are a solution to such… 

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