Harness Python for statistical arbitrage, exploiting market inefficiencies with quantitative models
In high-frequency trading, innovative strategies are key to profitability. One such approach, statistical arbitrage, leverages mathematical models to pinpoint and exploit market inefficiencies. Python, with its powerful computational capabilities, has become an essential tool for traders.
$ python -m venv --upgrade-deps --clear statarb_env
# On Linux/macOS, use
$ source statarb_env/bin/activate
# On Windows, use
$ statarb_env\Scripts\activate
$ pip install -U -r requirements.txt --no-cache-dir --disable-pip-version-check
$ jupyter lab --notebook-dir=.\notebooks --no-browserFeel free to fork this repo, open issues, or submit PRs. Ideas for additional models, new datasets, or better visualizations are always welcome 🙌
This project is licensed under the MIT License — feel free to use, modify, and share it as you like!
Made with 🐍 and ☕ by Swetank Mohanty Let’s connect on LinkedIn or X (formerly Twitter)