Optimally Rebalancing a Portfolio in Bloomberg, Entirely or Partly

We will learn how to use the portfolio optimization function of the PORT portfolio and risk analytics solution in Bloomberg to solve a classic problem in portfolio management: how to optimally rebalance an existing portfolio from a mean-variance optimality perspective. We will learn how to rebalance the entire portfolio, as well as how to do it with special consideration for one (or more) existing positions such as placeholder ETFs.

The specific example we will consider is rebalancing a previously-existing portfolio of the FAANG* stocks to mean-variance optimal positions, in the presence of an S&P500 ETF (SPY) that we want to treat separately.

This video assumes the viewer is familiar with mean-variance optimization from modern portfolio theory (MPT) and with the basics of entering a portfolio into the Bloomberg software.
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The FAANG portfolio is a group of high-performing tech stocks consisting of Facebook (FB), Amazon (AMZN), Apple (AAPL), Netflix (NFLX), and Alphabet (GOOGL). This portfolio is for illustration purposes only and is not intended as investment advice.