ebrahimpichka/DeepRL-trade
Algorithmic Trading Using Deep Reinforcement Learning algorithms (PPO and DQN)
This project helps quantitative traders and analysts automate stock trading decisions using advanced AI. It takes historical stock price data (like GOOG) and generates automated trading strategies based on deep reinforcement learning, outputting performance metrics to help you understand potential returns and risks. The primary users are individuals involved in quantitative finance who want to explore AI-driven trading algorithms.
Use this if you are a quantitative trader interested in experimenting with deep reinforcement learning algorithms (PPO and DQN) for autonomous stock trading and comparing their performance.
Not ideal if you are looking for a ready-to-deploy, production-grade trading system, as this is a research-oriented project focused on algorithm comparison.
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2
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Jupyter Notebook
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Last pushed
Feb 13, 2026
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