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.
Requirements
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.