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Algorithmic trading by reinforcement learning in a collaborative manner
DOI:10.1016/j.asoc.2026.115168.png)
Abstract
En 中文
• We propose an algorithmic trading method by combining RL with distributed learning. • A novel loss function integrating RL and imitation learning is proposed. • The proposed method outperforms several baselines on U.S. stock data. • The novel framework is flexible with various network architectures and RL agents.
Keywords:
Reinforcement Learning
Algorithmic Trading
Distributed Learning
Imitation Learning
Collaborative Framework
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W

