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.

语言：Jupyter Notebook · GitHub 星标：102 · Fork：36

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