Optimizing Automated Trading Systems with Deep Reinforcement Learning
In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward function, and learning algorithm for the cryptocu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/16/1/23 |