stochax 📈

A python package for the simulation and calibration of stochastic processes.

Minimal examples

Simulation

It can be used to simulate a stochastic process:

from stochax import ArithmeticBrownianMotion
abm = ArithmeticBrownianMotion(mu=0, sigma=0.5)
paths = abm.simulate(
    initial_value=0.5,
    n_steps=52,
    delta=1/52,
    n_simulations=100
)

Model fit

It is also possible to use the package to fit data:

import pandas as pd
from stochax import GeometricBrownianMotion

data = pd.read_csv('path/to/data.csv')
gbm = GeometricBrownianMotion()
res = gbm.calibrate(data)

print(res.get_summary())

Installation

To install the package the simplest procedure is:

pip install stochax

Now you can test the installation... In a python shell:

import stochax as sx

sx.__version__

Optional dependencies are docs for documentation and build for development. To install optional dependencies pip install stochax[docs,build].