Adversarial Deep Reinforcement Learning in Portfolio Management

29 Aug 2018 Zhipeng Liang Hao Chen Junhao Zhu Kangkang Jiang Yan-ran Li

In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)in portfolio management. All of them are widely-used in game playing and robot control... (read more)

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Methods used in the Paper


METHOD TYPE
Experience Replay
Replay Memory
Entropy Regularization
Regularization
Dense Connections
Feedforward Networks
Weight Decay
Regularization
ReLU
Activation Functions
Adam
Stochastic Optimization
Convolution
Convolutions
Batch Normalization
Normalization
DDPG
Policy Gradient Methods
PPO
Policy Gradient Methods