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# ffn - Financial Functions for Python

Alpha release - please let me know if you find any bugs!

If you are looking for a full backtesting framework, please check out [bt](https://github.com/pmorissette/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.

```python
import ffn
returns = ffn.get('aapl,msft,c,gs,ge', start='2010-01-01').to_returns().dropna()
returns.calc_mean_var_weights().as_format('.2%')
    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](https://pypi.python.org/pypi/ffn/)
using `pip`.

```bash
pip install ffn
```

Since ffn has many dependencies, we strongly recommend installing the [Anaconda Scientific Python Distribution](https://store.continuum.io/cshop/anaconda/). 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 http://pmorissette.github.io/ffn

- [Quickstart](http://pmorissette.github.io/ffn/quick.html)
- [Full API](http://pmorissette.github.io/ffn/ffn.html)