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Momentum is everywhere
even in ETF’s

June 14, 2016
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As featured in the Herald Sun – Friday 10th June 2016.
By David McCulloch – Market educator and consultant to Share Wealth Systems

In last week’s article, I discussed the concept of momentum as it relates to individual stocks. Speed and Mass are the two components that drive momentum and I gave the example of a snow ball rolling down a hill gathering even more speed as it grows larger with every roll. The exact same concept can also be applied to Exchange Traded Funds (ETF’s).

This concept is discussed in more detail in a book called, “The Ivy Portfolio” written by two money managers Mebane Faber and Eric Richardson. The book goes on to explain how the world’s best league schools were able to produce consistent returns of over 15% annually in their investment portfolios since 1985. Not only did they produce excellent returns, they also did it with greatly reduced volatility, (think highs and lows in ongoing account balance).

The findings of Faber and Richardson lead them to outline a similar strategy that could be used to mimic the Ivy league results and produce similar returns with very acceptable levels of drawdown. The core of the strategy is based on Relative Strength (momentum) and asset allocation. The selection of ETF’s are rotated at the end of each month depending on their relative strength over a specific look back period. The obvious questions are which ETF’s did they use and how did they measure the relative strength of each one? Great questions.

Five ETF’s were initially chosen to represent the broader markets that also gave a degree of diversification. The ETF’s chosen represented the Bond market (BND), the commodity index (DBC) the US stock market (VTI), the US Real estate sector(VNQ) and the rest of the world excluding the US (VEU). The relative strength of each ETF was then measured using several look back periods to take into account both shorter term and medium term performance.

Of the five ETF’s only the top three performing ones were chosen to be invested in for that month. The snowball concept once again comes in handy, in that momentum once underway is likely to continue into the near term future. At the end of the month the process is repeated and allocations altered if necessary.

A final part of the strategy was to apply what we call a filter. In this case the filter is a longer term moving average, and funds were only invested if the chosen ETF’s are also above that line. This makes sure that funds are not allocated to any ETF that isn’t outperforming its longer term average. You only need go back to the GFC to realise that having a simple exit strategy is one ways to preserve your capital. Funds not invested in any ETFs are held in cash. Fundamentals are driving the performance of each ETF over a period of time and it’s the technical analytics of this information that brings the model to life.

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