Skip to content

Latest commit

 

History

History
154 lines (101 loc) · 4.31 KB

README.rst

File metadata and controls

154 lines (101 loc) · 4.31 KB

Monte Carlo Simulator for Pandas Series

Python version PyPi version PyPi status Travis-CI build status Patreon Status Star this repo Follow me on twitter

pandas-montecarlo is a lightweight Python library for running simple Monte Carlo Simulations on Pandas Series data.

Changelog »


Quick Start

Let's run a monte carlo simulation on the returns of SPY (S&P 500 Spider ETF).

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

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%):

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

Plot simulations

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

demo

Show test stats

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

print(mc.maxdd)

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

Access raw simulations' DataFrame

print(mc.data.head())
    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:

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

Requirements

Legal Stuff

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

P.S.

Please drop me an note with any feedback you have.

Ran Aroussi