A reader submitted an ETF portfolio, asking for suggestions on how this could be improved. The gist of the question was how to use the Quantext Monte Carlo portfolio planner to improve the asset allocation. This portfolio is allocated fairly generically:
I entered the portfolio and allocations into the portfolio simulation model and the software tabulated historical data for the past three years on the ETF’s and developed parameters for simulating forward based on the long-term balance between risk and return in stocks and bonds. Using the parameters, the Monte Carlo model projected an average annual return of 10.9% per year for this portfolio, with a standard deviation in annual return (NYSE:SD) of 16% (relative to the projected SD for the S&P500 of 15.1%). The portfolio Beta is almost exactly 100%.
While this portfolio is ‘diversified’ from the perspective of style (large cap, medium cap, small cap, emerging markets, Euro markets, Pacific, energy, real estate), it is not particularly well diversified in terms of using portfolio offsets to manage risk.
By re-balancing funds among these ETF’s, the projected return improved by 1.35% per year, with the same level of total portfolio SD and a Beta of about 94%. The real improvements came, however, when we added allocations to individual stocks from companies for which fundamentals are not closely coupled to the returns in the broader market. By allocating part of the portfolio into insurance, health care and waste management stocks, the final portfolio yielded projected average annual return of 13.85%, with lower projected SD than the market as a whole and the original portfolio. The final portfolio is shown below (ETFs in yellow, individual stocks in green):
[This was the summary of a full paper that's available here (.pdf)]
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