Portfolio and risk analytics in Python
Jupyter Notebook Python
Clone or download
twiecki BLD Update requirements. Remove version string from setup.py as it's …
…handled by versioneer. Update release notes.
Latest commit 99463bc Aug 1, 2018

README.md

pyfolio

pyfolio

Join the chat at https://gitter.im/quantopian/pyfolio build status

pyfolio is a Python library for performance and risk analysis of financial portfolios developed by Quantopian Inc. It works well with the Zipline open source backtesting library.

At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple tear sheet analyzing a strategy:

simple tear 0 simple tear 1

Also see slides of a talk about pyfolio.

Installation

To install pyfolio, run:

pip install pyfolio

Development

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:

mkvirtualenv pyfolio

Next, clone this git repository and run python setup.py develop and edit the library files directly.

Bayesian tear sheet

Generating a Bayesian tearsheet requires PyMC3 and Theano. You can install these packages with the following commands:

pip install theano
pip install pymc3

Matplotlib on OSX

If you are on OSX and using a non-framework build of Python, you may need to set your backend:

echo "backend: TkAgg" > ~/.matplotlib/matplotlibrc

Usage

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:

jupyter notebook

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.

Questions?

If you find a bug, feel free to open an issue in this repository.

You can also join our mailing list or our Gitter channel.

Support

Please open an issue for support.

Contributing

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.