Scikit Risk

A python library to perform Monte Carlo probabilistic modeling and risk analysis.

Installation

Preferably, create a virtual environment and install scikit-risk by running

pip install scikit-risk

Note that scikit-risk is only available in python 3.

We are currently in active development so we are aiming for the latest versions of each dependency. As soon as a stable version is established, dependencies with particular versions will be indicated.

Setup a development environment

Two things to note for those wishing to participate in scikit-risk development:

1. Github flow is being used as a working method.

   That is, you create a project fork from https://github.com/qu4nt/scikit-risk, to propose any change you create a new branch from this repository and add a Pull Request directly from this new branch.

2. To create a development environment you have to clone the repository locally, create a development environment, activate it, and run:

   pip install -e .

   From the root folder of scikit-risk

Authors

Team qu4nt

• Francisco Palm, [email protected]
• Rainer Palm, [email protected]
• Lino Urdaneta, [email protected]
• Mariangela Petrizzo, [email protected]
• Adriana Tiso, [email protected]

You?