Metadata-Version: 2.1
Name: fullmonte
Version: 0.0.4
Summary: A monte carlo simulation for extrapolated returns.
Home-page: https://github.com/8W9aG/fullmonte
Author: Will Sackfield
Author-email: will.sackfield@gmail.com
License: MIT
Keywords: monte carlo
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.0.3
Requires-Dist: numpy>=1.25.2
Requires-Dist: matplotlib>=3.8.3

# fullmonte

<a href="https://pypi.org/project/fullmonte/">
    <img alt="PyPi" src="https://img.shields.io/pypi/v/fullmonte">
</a>

Monte Carlo simulations for extrapolated returns.

## Dependencies :globe_with_meridians:

Python 3.11.6:

- [numpy 1.25.2](https://numpy.org/)
- [pandas 2.0.3](https://pandas.pydata.org/)
- [matplotlib 3.8.3](https://matplotlib.org/)

## Raison D'être :thought_balloon:

fullmonte is a python library that implements the simulation and plotting of a monte carlo run on a financial return assuming normal distributions.

## Installation :inbox_tray:

This is a python package hosted on pypi, so to install simply run the following command:

`pip install fullmonte`

## Usage example :eyes:

A quick example of how to use this library is the following:

```python
from fullmonte import simulate, plot

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Create some test data with a $100,000 initial investment
pct_ret = np.random.uniform(-0.1, 0.1, 252 * 10)
ret = np.concatenate((np.array([100000.0]), pct_ret + 1.0)).cumprod()
# Simulate monte carlo
df = simulate(pd.Series(ret))
print(df)
# Plot the monte carlo simulations
plot(df)
plt.show()
```

This will produce the following:

![Monte Carlo](mc.png "Monte Carlo")

## License :memo:

The project is available under the [MIT License](LICENSE).
