Sharif Digital Repository

Algorithmic trading in financial markets with machine learning is a developing and promising field of research. Financial markets have a complex, uncertain, and dynamic nature, making them challenging for algorithmic trading. To cope with the challenges of algorithmic trading in financial markets, we propose a multi-agent deep reinforcement learning framework trained by Deep Q-learning (DQN) algorithm to perform financial trading. This framework consists of multiple cooperative agents, each of which trained on a specific timeframe, to perform financial trading on the collective intelligence of the agents. Numerical experiments are conducted on historical data of the EUR/USD currency pair....