Application of deep reinforcement learning in stock trading strategies and stock forecasting

• Published in: Computing Vol. 102; no. 6; pp. 1305 - 1322
• Main Authors: Li, Yuming, Ni, Pin, Chang, Victor
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.06.2020; Springer Nature B.V
• Subjects: Artificial Intelligence; Computer Appl. in Administrative Data Processing; Computer Communication Networks; Computer Science; Decision making; Decision theory; Deep learning; Economic forecasting; Information Systems Applications (incl.Internet); Mathematical models; Securities markets; Signal processing; Software Engineering; 68T01; Deep Q learning; 91G10; Financial strategy; Reinforcement learning
• ISSN: 0010-485X; 1436-5057
• DOI: 10.1007/s00607-019-00773-w

The role of the stock market across the overall financial market is indispensable. The way to acquire practical trading signals in the transaction process to maximize the benefits is a problem that has been studied for a long time. This paper put forward a theory of deep reinforcement learning in th...