A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning

Ruoyu Sun, Yue Xi, Angelos Stefanidis +2

Deep Reinforcement Learning (DRL) has been extensively used to address portfolio optimization problems. The DRL agents acquire knowledge and make decisions through unsupervised int…