Monte Carlo Simulator for Pandas Series

.. image:: https://img.shields.io/badge/python-3.4+-blue.svg?style=flat :target: https://pypi.python.org/pypi/pandas-montecarlo :alt: Python version

.. image:: https://img.shields.io/pypi/v/pandas-montecarlo.svg?maxAge=60 :target: https://pypi.python.org/pypi/pandas-montecarlo :alt: PyPi version

.. image:: https://img.shields.io/pypi/status/pandas-montecarlo.svg?maxAge=60 :target: https://pypi.python.org/pypi/pandas-montecarlo :alt: PyPi status

.. image:: https://img.shields.io/travis/ranaroussi/pandas-montecarlo/master.svg?maxAge=1 :target: https://travis-ci.org/ranaroussi/pandas-montecarlo :alt: Travis-CI build status

.. image:: https://img.shields.io/badge/Patreon-accepting-ff69b4.svg?style=flat :target: https://www.patreon.com/aroussi :alt: Patreon Status

.. image:: https://img.shields.io/github/stars/ranaroussi/pandas-montecarlo.svg?style=social&label=Star&maxAge=60 :target: https://github.com/ranaroussi/pandas-montecarlo :alt: Star this repo

.. image:: https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60 :target: https://twitter.com/aroussi :alt: Follow me on twitter

\

pandas-montecarlo is a lightweight Python library for running simple Monte Carlo Simulations <https://en.wikipedia.org/wiki/Monte_Carlo_method>_ on Pandas Series data.

Changelog » <./CHANGELOG.rst>__

Quick Start

Let's run a monte carlo simulation on the returns of SPY <https://finance.yahoo.com/quote/SPY>_ (S&P 500 Spider ETF).

First, let's download SPY's data and calculate the daily returns.

.. code:: python

from pandas_datareader import data

df = data.get_data_yahoo("SPY")
df['return'] = df['Adj Close'].pct_change().fillna(0)

Next, we'll import pandas_montecarlo and run monte carlo simulation with 10 simulations (for demo simplifications) and bust/max drawdown set to -10.0% and goal threshhold set to +100.0% (defaults is >=0%):

.. code:: python

import pandas_montecarlo
mc = df['return'].montecarlo(sims=10, bust=-0.1, goal=1)

Plot simulations

.. code:: python

mc.plot(title="SPY Returns Monte Carlo Simulations")  # optional: , figsize=(x, y)

.. image:: https://raw.githubusercontent.com/ranaroussi/pandas-montecarlo/master/demo.png :width: 640 px :height: 360 px :alt: demo

Show test stats

.. code:: python

print(mc.stats)

# prints
{
    'min':    0.98088401987146789,
    'max':    0.98088401987146934,
    'mean':   0.98088401987146911,
    'median': 0.98088401987146911,
    'std':    4.0792198665315552e-16,
    'maxdd': -0.17221175099828012,  # max drawdown
    'bust':   0.2,  # probability of going bust
    'goal':   0.0   # probability of reaching 100% goal
}

Show bust / max drawdown stats

.. code:: python

print(mc.maxdd)

# prints
{
    'min':    -0.27743285515585991,
    'max':    -0.00031922711279186444,
    'mean':   -0.07888087155686732,
    'median': -0.06010335858432081,
    'std':     0.062172124557467685
}

Access raw simulations' DataFrame

.. code:: python

print(mc.data.head())

.. code:: text

    original          1          2          3          4  ...       10
0   0.000000   0.017745  -0.002586  -0.005346  -0.042107  ...  0.00139
1   0.002647   0.000050   0.000188   0.010141   0.007443  ...  0.00108
2   0.000704   0.002916   0.005324   0.000073  -0.003238  ...  0.00071
3   0.004221   0.008564   0.001397   0.007950  -0.006392  ...  0.00902
4   0.003328  -0.000511   0.005123   0.013491  -0.005105  ...  0.00252

Installation

Install pandas_montecarlo using pip:

.. code:: bash

$ pip install pandas_montecarlo --upgrade --no-cache-dir

Requirements

• Python <https://www.python.org>_ >=3.4
• Pandas <https://github.com/pydata/pandas>_ (tested to work with >=0.18.1)
• Matplotlib <https://matplotlib.org>_ (tested to work with >=1.5.3)

Legal Stuff

pandas-montecarlo is distributed under the GNU Lesser General Public License v3.0. See the LICENSE.txt <./LICENSE.txt>_ file in the release for details.

P.S.

Please drop me an note with any feedback you have.

Ran Aroussi