Tools for investing in Python

Related tags

Deep Learningpythoninvestingportfolio-optimization
Overview

InvestOps

Original repository on GitHub

Original author is Magnus Erik Hvass Pedersen

Introduction

This is a Python package with simple and effective tools for investing, including the following:

  • Portfolio diversification using the so-called "Hvass Diversification" algorithm, which is extremely fast to compute and very robust to estimation errors in the correlation matrix. (Tutorial) (Paper)

The InvestOps Python package is a distilled version of some of the research from the FinanceOps project, whose papers can be found on SSRN and GitHub.

Tutorials

Tutorials are made as Python Notebooks which can be modified and run entirely on the internet or on your own computer.

Installation

It is best to use a virtual environment when installing Python packages, so you can easily delete the environment again if something goes wrong. You write the following in a Linux terminal:

virtualenv investops-env

Or you can use Anaconda instead of a virtualenv:

conda create --name investops-env python=3

Then you switch to the virtual environment:

source activate investops-env

And then you can install the InvestOps package inside that virtual environment:

pip install investops

You can now import the InvestOps package in your Python program as follows:

import investops as iv

# Print the InvestOps version.
print(iv.__version__)

License (MIT)

This is published under the MIT License which allows very broad use for both academic and commercial purposes.

You are very welcome to modify and use this source-code in your own project. Please keep a link to the original repository.

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