Portfolio Management using Deep Reinforcement Learning

arXiv:2405.01604v1 Announce Type: cross
Abstract: Algorithmic trading or Financial robots have been conquering the stock markets with their ability to fathom complex statistical trading strategies. But with the recent development of deep learning technologies, these strategies are becoming impotent. The DQN and A2C models have previously outperformed eminent humans in game-playing and robotics. In our work, we propose a reinforced portfolio manager offering assistance in the allocation of weights to assets. The environment proffers the manager the freedom to go …

abstract arxiv cs.lg deep learning development financial game humans management markets playing portfolio q-fin.pm reinforcement reinforcement learning robotics robots statistical stock stock markets strategies technologies trading type