This story covers:

1. What is a Markowitz mean/variance-optimised portfolio
2. How to compute one using Python (GitHub source code provided)
3. How to back-test your strategy against an established market-traded fund
   The objective of this experiment is to see whether we can use concepts from 1952 to create a passive portfolio that would do better than today’s “top-performing” exchange-traded funds (ETFs).
   Disclaimer: this is merely a numerical and computational exercise and should in no way be treated as investment advice or any foundation for such.
   Foreword
   To find a worthy competitor, I googled “best passive tech ETF”, followed the first link and chose the number one-ranked fund — I do not know if I am allowed to refer to its official name here on Medium — let us call it Fund X. Fund X specialises in equities listed on the major North American exchanges in the tech and software industries and (as of 09.06.2020) is invested into 104 individual stocks. I have downloaded the performance of all US equities from here, kindly provided by the Kaggle community, and filtered for the fund’s positions.

#asset-management #asset-allocation #efficient-frontier #python #stocks