Enhancing Cross-Sectional Currency Strategies by Context-Aware Learning to Rank with Self-Attention
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Cited by:
- Kieran Wood & Sven Giegerich & Stephen Roberts & Stefan Zohren, 2021. "Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture," Papers 2112.08534, arXiv.org, revised Nov 2022.
- Daniel Poh & Stephen Roberts & Stefan Zohren, 2022. "Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity," Papers 2208.09968, arXiv.org, revised Feb 2023.
- Wee Ling Tan & Stephen Roberts & Stefan Zohren, 2024. "Deep Learning for Options Trading: An End-To-End Approach," Papers 2407.21791, arXiv.org.
- Daiya Mita & Akihiko Takahashi, 2022. "Multi-Agent Model Based Proactive Risk Management For Equity Investment," CIRJE F-Series CIRJE-F-1207, CIRJE, Faculty of Economics, University of Tokyo.
- Nozomu Kobayashi & Yoshiyuki Suimon & Koichi Miyamoto & Kosuke Mitarai, 2023. "The cross-sectional stock return predictions via quantum neural network and tensor network," Papers 2304.12501, arXiv.org, revised Feb 2024.
- Wee Ling Tan & Stephen Roberts & Stefan Zohren, 2023. "Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies," Papers 2302.10175, arXiv.org.
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