Mbt-gym: Reinforcement learning for model-based limit order book trading-Reference-Cited by-同舟云学术

Mbt-gym: Reinforcement learning for model-based limit order book trading

Published:2023-11-25 Issue: Volume: Page:
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Container-title:4th ACM International Conference on AI in Finance
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Author:

Jerome Joseph¹^ORCID,Sánchez-Betancourt Leandro²^ORCID,Savani Rahul³^ORCID,Herdegen Martin⁴^ORCID

Affiliation:

1. Department of Computer Science, University of Liverpool, United Kingdom

2. Mathematical Institute and Oxford-Man Institute of Quantitative Finance, University of Oxford, United Kingdom

3. Department of Computer Science, University of Liverpool, United Kingdom and The Alan Turing Institute, United Kingdom

4. Department of Statistics, University of Warwick, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604237.3626873

Reference58 articles.

1. Algorithmic trading in a microstructural limit order book model

2. Optimal Trading with Stochastic Liquidity and Volatility

3. Optimal execution of portfolio transactions

4. Selim Amrouni , Aymeric Moulin , Jared Vann , Svitlana Vyetrenko , Tucker Balch , and Manuela Veloso . 2021. ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets. arXiv:2110.14771 ( 2021 ). Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, and Manuela Veloso. 2021. ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets. arXiv:2110.14771 (2021).

5. High-frequency trading in a limit order book

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