Review on Financial Trading System Based on Reinforcement Learning
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National Natural Science Foundation of China (71531012)

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    Abstract:

    In recent years, reinforcement learning has made great progress in the fields of electronic games, chess, and decision-making control. It has also driven the rapid development of financial transaction systems. The issue of financial transactions has become a hot topic in the field of reinforcement learning. Especially, it has wide application demand and academic research significance in the fields of stock, foreign exchange, and futures. This paper summarizes the research achievements of transaction systems, adaptive algorithms, and transaction strategies based on the progress of reinforcement learning models, which are commonly used in the financial field. Finally, the difficulties and challenges of reinforcement learning in financial trading system are discussed, and the future development trend is prospected.

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梁天新,杨小平,王良,韩镇远.基于强化学习的金融交易系统研究与发展.软件学报,2019,30(3):845-864

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History
  • Received:July 19,2018
  • Revised:September 20,2018
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  • Online: March 06,2019
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