.. image:: https://media.quantopian.com/logos/open_source/alphalens-logo-03.png :align: center

Alphalens ========= .. image:: https://github.com/quantopian/alphalens/workflows/CI/badge.svg :alt: GitHub Actions status :target: https://github.com/quantopian/alphalens/actions?query=workflow%3ACI+branch%3Amaster

Alphalens is a Python Library for performance analysis of predictive (alpha) stock factors. Alphalens works great with the Zipline <https://www.zipline.io/>__ open source backtesting library, and Pyfolio <https://github.com/quantopian/pyfolio>__ which provides performance and risk analysis of financial portfolios. You can try Alphalens at Quantopian <https://www.quantopian.com>_ -- a free, community-centered, hosted platform for researching and testing alpha ideas. Quantopian also offers a fully managed service for professionals <https://factset.quantopian.com>_ that includes Zipline, Alphalens, Pyfolio, FactSet data, and more.

The main function of Alphalens is to surface the most relevant statistics and plots about an alpha factor, including:

• Returns Analysis
• Information Coefficient Analysis
• Turnover Analysis
• Grouped Analysis

With a signal and pricing data creating a factor "tear sheet" is a two step process:

.. code:: python

import alphalens # Ingest and format data factordata = alphalens.utils.getcleanfactorandforwardreturns(my_factor, pricing, quantiles=5, groupby=ticker_sector, groupbylabels=sectornames)

# Run analysis alphalens.tears.createfulltearsheet(factordata)

Learn more

Check out the example notebooks <https://github.com/quantopian/alphalens/tree/master/alphalens/examples>__ for more on how to read and use the factor tear sheet. A good starting point could be this <https://github.com/quantopian/alphalens/tree/master/alphalens/examples/alphalenstutorialonquantopian.ipynb>_

Installation

Install with pip:

::

pip install alphalens

Install with conda:

::

conda install -c conda-forge alphalens

Install from the master branch of Alphalens repository (development code):

::

pip install git+https://github.com/quantopian/alphalens

Alphalens depends on:

• matplotlib <https://github.com/matplotlib/matplotlib>__
• numpy <https://github.com/numpy/numpy>__
• pandas <https://github.com/pandas-dev/pandas>__
• scipy <https://github.com/scipy/scipy>__
• seaborn <https://github.com/mwaskom/seaborn>__
• statsmodels <https://github.com/statsmodels/statsmodels>__

A good way to get started is to run the examples in a Jupyter notebook <https://jupyter.org/>__.

To get set up with an example, you can:

Run a Jupyter notebook server via:

.. code:: bash

jupyter notebook

From the notebook list page(usually found at `http://localhost:8888/), navigate over to the examples directory, and open any file with a .ipynb extension.

If you find a bug, feel free to open an issue on our github tracker __.

If you want to contribute, a great place to start would be the help-wanted issues __.

• Andrew Campbell __
• James Christopher __
• Thomas Wiecki __
• Jonathan Larkin __
• Jessica Stauth (jstauth@quantopian.com)
• Taso Petridis _