fortitudo-tech 0.10.1

Investment and risk technologies maintained by Fortitudo Technologies.

Fortitudo Technologies Open Source

This package allows you to explore open-source implementations of some of our fundamental technologies, e.g., Entropy Pooling and CVaR optimization in Python.

The package is intended for advanced users who are comfortable specifying portfolio constraints and Entropy Pooling views using matrices and vectors. This gives full flexibility in relation to working with these technologies. Hence, input checking is intentionally kept to a minimum.

Fortitudo Technologies offers novel investment software as well as quantitative and digitalization consultancy to the investment management industry. For more information, please visit our website.

Installation Instructions

Installation can be done via pip:

pip install fortitudo.tech

For best performance, we recommend that you install the package in a conda environment and let conda handle the installation of dependencies before installing the package using pip. You can do this by following these steps:

conda create -n fortitudo.tech -c conda-forge python=3.11 scipy pandas=1.5 matplotlib cvxopt
conda activate fortitudo.tech
pip install fortitudo.tech

The examples might require you to install additional packages, e.g., seaborn and ipykernel / notebook / jupyterlab if you want to run the notebooks. Using pip to install these packages should not cause any dependency issues.

You can also explore the examples in the cloud without any local installations using Binder. However, note that Binder servers have very limited ressources and might not support some of the optimized routines this package uses. For best performance, you should install the package on a machine that supports the Math Kernel Library.

Disclaimer

This package is completely separate from our proprietary solutions and therefore not representative of neither the quality nor the functionality offered by the Simulation Engine and Investment Analysis modules. If you are an institutional investor who wants to experience how these methods can be used for sophisticated analysis in practice, please request a demo by sending an email to [e-mail].