Deep Direct Reinforcement Learning for Financial Signal Representation and Trading

• Published in: IEEE transaction on neural networks and learning systems Vol. 28; no. 3; pp. 653 - 664
• Main Authors: Deng, Yue, Bao, Feng, Kong, Youyong, Ren, Zhiquan, Dai, Qionghai
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Back propagation; Deep learning (DL); Feature extraction; financial signal processing; Learning (artificial intelligence); Machine learning; neural network (NN) for finance; Neural networks; Optimization; Reinforcement; reinforcement learning (RL); Representations; Robustness; Signal representation; Training; Unknown environments

Can we train the computer to beat experienced traders for financial assert trading? In this paper, we try to address this challenge by introducing a recurrent deep neural network (NN) for real-time financial signal representation and trading. Our model is inspired by two biological-related learning...