theanh97 / Deep-Reinforcement-Learning-with-Stock-Trading

This project uses Deep Reinforcement Learning (DRL) to develop and evaluate stock trading strategies. By implementing agents like PPO, A2C, DDPG, SAC, and TD3 in a realistic trading environment with transaction costs, it aims to optimize trading decisions based on return, volatility, and Sharpe ratio.
44Updated 4 months ago

Related projects

Alternatives and complementary repositories for Deep-Reinforcement-Learning-with-Stock-Trading