Deep Reinforcement Learning for Stock Trading

A simple Deep Reinforcement Learning for Stock Trading is a Python project that uses a Deep Q-Network (DQN) agent to predict stock prices and make trading decisions.

Installation

Clone this repository and install the required dependencies.

git clone https://github.com/Peterpetu/DeepReinforcementStock.git

pip install -r requirements.txt

Usage

After cloning the repository and installing the dependencies, you can train the DQN agent using the train_agent.py script.

python train_agent.py

After training the DQN agent, you can test it using the test_agent.py script.

python test_agent.py

This will load the trained model and test it on the test data. The agent's decisions and the total rewards will be printed to the console.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT