Portfolio Builder Update January 2017 – Markowitz Modern Portfolio Theory

As previously announced, we´re updating our Portfolio Builder Optimization periodically, both in the Online and Offline Version.

Updated Portfolio Builder Optimization for 2017

Why that? Recall the Portfolio Builder is using a Markowitz Modern Portfolio Theory approach, that is, we´re using past returns, volatilities and co-variances to determine an optimum fixed-weight allocation among our different strategies under certain rules: either to Maximize the Sharpe Ratio (Risk/Return), target a volatility level one feels comfortable with, or to limit historical drawdown in the expectation this will also hold true for the future.

Using Markowitz Modern Portfolio Theory

While full-blooded Markowitz aficionados will now probably feel the urgent need to stone us to death, yes, same to some other peers in the industry ,our approach is dynamic and we do not feel the past is set in .. hmm.. stone. As such, we need to update our Portfolio Builder Optimization periodically based on the most recent returns, volatilities and co-variances of and between our strategies.

As the overall optimization is based on data from the past eight years and we´re only adding the last quarter of data, the changes are relatively small as you can see in the following.

2016 results of our 10 Portfolios for everybody

But before going into the allocations for 2017, how was the performance of the 10 “pre-configured” Portfolio´s during 2016? Results using our Online Portfolio Builder are as follows:

performance-2016

But overall with all Portfolios in the double-digit area, six of ten Portfolios topping 20% in returns and all but the minimum Volatility Portfolio exceeding the 12% return of the S&P 500, the conclusion of a partly bumpy year with many surprises is excellent. It pays out to be diversified over low correlated strategies. Looking for a pattern in the individual under or over performance to their historical average, especially strategies with a high bond allocation suffered in the last half due to the anticipated FED hike and the “Trump effect” for higher inflation expectations due to a significant public spending program. On the sweet side, strategies with high equity exposure had either a great run following the January/February 2016 recovery, or benefited from the strong exposure to NASDAQ in the last two months of the year.

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