Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning
作者：
Highlights：
• A financial trading system is proposed to improve traders’ profits.
• The system uses the number of shares, action strategies, and transfer learning.
• The number of shares is determined by using a DNN regressor.
• When confusion exists, postponing a financial decision is the best policy.
• Transfer learning can address problems of insufficient financial data.
摘要
•A financial trading system is proposed to improve traders’ profits.•The system uses the number of shares, action strategies, and transfer learning.•The number of shares is determined by using a DNN regressor.•When confusion exists, postponing a financial decision is the best policy.•Transfer learning can address problems of insufficient financial data.
论文关键词：Reinforcement learning,Deep Q-learning,Stock trading,Trading strategy,Transfer learning
论文评审过程：Received 10 June 2018, Revised 20 August 2018, Accepted 16 September 2018, Available online 20 September 2018, Version of Record 29 September 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.036
