I would like to take the opportunity to ask for your help on an assignment I'm trying to complete.
For this 'Modern Robo Advisory' course we are asked to solve a (target) goal-based investment challenge in Python which consists in finding the optimal mix (weights) of securities 1 and 2 (securities 1: bonds & 2: structured notes) to achieve at least 10% of returns after 3,4 and 5 years using Mean-Variance Optimization (MVO).
We were given two 1824 (trading days) X 2000 (columns of the security) data sets which are 5 years of daily returns. The column of the data set of bonds and the data set of structured notes are to be taken together as a simulated 2-asset portfolio scenario.
My question is the following: I know how to run an MVO on 2 or more assets with historical returns and find out which is the optimal weight mix to achieve a given % of returns. But in this case, I cannot seem to wrap my head around as to how I would go about running an MVO on 2000 pairs of assets and then deduce the optimal mix of weights.
Thanks in advance for your help