Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit

Zhu, Mengying; Zheng, Xiaolin; Wang, Yan; Liang, Qianqiao; Zhang, Wenfang

doi:10.24963/ijcai.2020/646

Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit

Mengying Zhu, Xiaolin Zheng, Yan Wang, Qianqiao Liang, Wenfang Zhang

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Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. Special Track on AI in FinTech. Pages 4682-4689.

https://doi.org/10.24963/ijcai.2020/646

Keywords

Foundation for AI in FinTech: Reinforcement learning for FinTech
AI for trading: General
AI for trading: AI for portfolio analytics
AI for trading: AI for strategic trading and strategy design

Abstract

Online portfolio selection (OLPS) is a fundamental and challenging problem in financial engineering, which faces two practical constraints during the real trading, i.e., cardinality constraint and non-zero transaction costs. In order to achieve greater feasibility in financial markets, in this paper, we propose a novel online portfolio selection method named LExp4.TCGP with theoretical guarantee of sublinear regret to address the OLPS problem with the two constraints. In addition, we incorporate side information into our method based on contextual bandit, which further improves the effectiveness of our method. Extensive experiments conducted on four representative real-world datasets demonstrate that our method significantly outperforms the state-of-the-art methods when cardinality constraint and non-zero transaction costs co-exist.

Mengying Zhu, Xiaolin Zheng, Yan Wang, Qianqiao Liang, and Wenfang Zhang. 2020. Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20. IJCAI, 4682–4689. https://doi.org/10.24963/ijcai.2020/646

@inproceedings{ijcai2020p646,
  title     = {Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit},
  author    = {Zhu, Mengying and Zheng, Xiaolin and Wang, Yan and Liang, Qianqiao and Zhang, Wenfang},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
               Artificial Intelligence, {IJCAI-20}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Christian Bessiere},
  pages     = {4682--4689},
  year      = {2020},
  month     = {7},
  note      = {Special Track on AI in FinTech},
  doi       = {10.24963/ijcai.2020/646},
  url       = {https://doi.org/10.24963/ijcai.2020/646},
}

TY  - CPAPER
TI  - Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit
AU  - Zhu, Mengying
AU  - Zheng, Xiaolin
AU  - Wang, Yan
AU  - Liang, Qianqiao
AU  - Zhang, Wenfang
T2  - Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2020
SP  - 4682
EP  - 4689
DO  - 10.24963/ijcai.2020/646
UR  - https://doi.org/10.24963/ijcai.2020/646
ER  -