An Application of Deep Reinforcement Learning to Algorithmic Trading

7 Apr 2020 Thibaut Théate Damien Ernst

This scientific research paper presents an innovative approach based on deep reinforcement learning (DRL) to solve the algorithmic trading problem of determining the optimal trading position at any point in time during a trading activity in stock markets. It proposes a novel DRL trading strategy so as to maximise the resulting Sharpe ratio performance indicator on a broad range of stock markets... (read more)

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