ffn - Financial Functions for Python

If you are looking for a full backtesting framework, please check out bt. bt is built atop ffn and makes it easy and fast to backtest quantitative strategies.

Overview

ffn is a library that contains many useful functions for those who work in quantitative finance. It stands on the shoulders of giants (Pandas, Numpy, Scipy, etc.) and provides a vast array of utilities, from performance measurement and evaluation to graphing and common data transformations.

import ffn
returns = ffn.get('aapl,msft,c,gs,ge', start='2010-01-01').to_returns().dropna()
print(returns.calc_mean_var_weights().as_format('.2%'))

Example output:

    aapl    62.54%
    c       -0.00%
    ge      36.19%
    gs      -0.00%
    msft     1.26%
    dtype: object

Installation

The easiest way to install ffn is from the Python Package Index using pip.

pip install ffn

Since ffn has many dependencies, we strongly recommend installing the Anaconda Scientific Python Distribution. This distribution comes with many of the required packages pre-installed, including pip. Once Anaconda is installed, the above command should complete the installation.

Documentation

Read the docs at https://pmorissette.github.io/ffn/.

• Introduction

• Installation guide

• Quickstart

• Full API

Contribute

See the development guide for setup, tests, documentation builds, and Copier template updates.