Factor Representation and Decision Making in Stock Markets Using Deep Reinforcement Learning

Deep Reinforcement learning is a branch of unsupervised learning in which an agent learns to act based on environment state in order to maximize its total reward. Deep reinforcement learning provides good opportunity to model the complexity of portfolio choice in high-dimensional and data-driven env...

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Hauptverfasser:	Dong, Zhaolu, Huang, Shan, Ma, Simiao, Qian, Yining
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Quantitative Finance - Statistical Finance
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