Performance and risk analysis of financial portfolios with Python
pyfolio is a Python library for performance and risk analysis of financial portfolios that works well with the Zipline open source backtesting library.
Trading Strategy Analysis with pyfolio
At the core of pyfolio are various tear sheets that combine various individual plots and summary statistics to provide a comprehensive view of the performance of a trading algorithm.
Here's an example of a simple tear sheet analyzing a strategy executed with the Zipline backtesting engine:
The tear sheet presents performance and risk metrics for the strategy separately during the backtest and out-of-sample periods:
In addition, it visualizes how several risk and return metrics behave over time:
To install pyfolio, run:
pip install pyfolio-reloaded
conda install -c ml4t pyfolio-reloaded
For development, you may want to use a virtual environment to avoid dependency conflicts between pyfolio and other Python projects you have.
To get set up with a virtual env, run:
Next, clone this git repository and run
python -m pip install .[all] and edit the library files directly.
A good way to get started is to run the pyfolio examples in a Jupyter notebook. To do this, you first want to start a Jupyter notebook server:
From the notebook list page, navigate to the pyfolio examples directory and open a notebook. Execute the code in a notebook cell by clicking on it and hitting Shift+Enter.
If you find a bug, feel free to open an issue in this repository.
You can also join our community.
Please open an issue for support.
If you'd like to contribute, a great place to look is the issues marked with help-wanted.
For a list of core developers and outside collaborators, see the GitHub contributors list.
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