estimation errors

We use unsupervised machine learning to cluster stocks into equally weighted portfolios which in turn are plugged into minimum variance optimization.

Ranking assets based on their expected returns and subsequently optimizing portfolios on the reduced amount of information produces pobetter forecasts and significantly improved out-of-sample performance related to the plug-in portfolio.