This repository contains a Jupyter Notebook for a trading bot developed using the Financial Reinforcement Learning (FinRL) framework, specifically designed to work with the Dow 30 stocks. The bot follows a systematic approach to trading, integrating financial data handling, preprocessing, model training, and potentially executing trades via the Alpaca API.
The trading bot notebook recreates the necessary steps to:
- Fetch financial data from the Dow 30 stocks list.
- Preprocess the data by adding technical indicators and risk management metrics.
- Set up the model environment.
- Train the model to execute trades based on learned strategies.
Before running this notebook, ensure you have the following:
- Python 3.8 or later.
- Jupyter Notebook or JupyterLab installed.
- Necessary Python libraries which can be installed via requirements file (if provided) or through pip:
pip install -r requirements.txt
To get started with this trading bot, follow these steps:
- Clone the repository to your local machine
- Install the required dependencies:
pip install -r requirements.txt
- Open the Jupyter Notebook in your Jupyter environment:
jupyter notebook trading_bot_v2.ipynb