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Practical Deep Reinforcement Learning Approach for Stock Trading. (arXiv:1811.07522v3 [cs.LG] UPDATED)
Aug. 2, 2022, 2:12 a.m. | Xiao-Yang Liu, Zhuoran Xiong, Shan Zhong, Hongyang Yang, Anwar Walid
stat.ML updates on arXiv.org arxiv.org
Stock trading strategy plays a crucial role in investment companies. However,
it is challenging to obtain optimal strategy in the complex and dynamic stock
market. We explore the potential of deep reinforcement learning to optimize
stock trading strategy and thus maximize investment return. 30 stocks are
selected as our trading stocks and their daily prices are used as the training
and trading market environment. We train a deep reinforcement learning agent
and obtain an adaptive trading strategy. The agent's performance …
arxiv learning lg reinforcement reinforcement learning stock trading
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