Deep Reinforcement Learning for Quantitative Trading: Challenges and Opportunities

Author:

An Bo1ORCID,Sun Shuo1ORCID,Wang Rundong1ORCID

Affiliation:

1. Nanyang Technological University, Singapore

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications

Reference14 articles.

1. Robust Market Making via Adversarial Reinforcement Learning

2. Model-based deep reinforcement learning for dynamic portfolio optimization;yu,2019

3. A Comprehensive Survey on Graph Neural Networks

4. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading

5. Get real: Realism metrics for robust limit order book market simulations;vyetrenko,2019

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