Portfolio Construction and Optimization with Python

Learn how to construct and optimize a Portfolio using Python

What is this course about?

What you’ll learn

  • Learn to calculate Risk adjusted Portfolio returns.
  • Learn to Optimize portfolio weights.
  • Learn to leverage Matrix Algebra to construct an Optimal Portfolio.
  • Apply Finance Theory to Practice.

Course Content

  • Introduction –> 2 lectures • 12min.
  • Understanding Matrix operations –> 7 lectures • 19min.
  • Optimize Portfolio weights using Matrix Algebra –> 7 lectures • 24min.

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What is this course about?

In this 1 hour crash course I am going over the whole process of setting up a Portfolio Optimization with Python step by step. I am doing it hands on showing all calculation steps besides to get the best understanding of all steps involved possible.


You will learn:

– How stock returns are calculated and why log returns are used

– How to pull stock prices and calculate relevant metrics

– How to calculate Portfolio Return and Variance (/Portfolio risk)

– How to compare a Portfolio of weighted assets with single assets

– How to build a whole Optimization by minimizing the Sharpe Ratio (risk adjusted return)

– How to build a Optimization from scratch (besides using a solver)

– How to split your dataset so that you optimize on seen data and test on unseen data


Why should I be your constructor?

I got years of experience coding in Python both teaching but also several years of actually working in the field.

Besides currently working in the field I wrote my Master Thesis on a quantitative Finance topic and got a YouTube channel teaching Algorithmic Trading and Data Science hands-on tutorials with over 75.000 subscribers.


Why this course?

This course is giving you a non-time wasting hands-on approach on Portfolio Optimization with Python.


Any questions coming up?

If you got any questions please feel free to reach out! I am happy to hear from you.

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