theanh97 / Deep-Reinforcement-Learning-with-Stock-TradingView external linksLinks
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.
☆95Jun 28, 2024Updated last year
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