Dynamic Asset Allocation for Practitioners Part 1: The Many Faces of Momentum

June 1st, 2013

by Adam Butler, Mike Philbrick, Rodrigo Gordillo

A (Very) Short History of Dynamic Asset Allocation

The field of tactical or dynamic asset allocation has grown dramatically since Mebane Faber published what is perhaps the first broadly accessible paper on the topic in 2007, 'A Quantitative Approach to Tactical Asset Allocation'. Faber's original paper utilized a simple 10 month moving average as a signal to move into or out of a basket of 5 major global asset classes. Over the period 1970 through the paper's 2009 update, this technique generated better returns than any of the individual assets in the sample universe - U.S. and EAFE stocks, U.S. real estate, Treasuries and commodities - and with substantially lower risk than the equal weight basket or a 60/40 stock/Treasury portfolio.

In 2009 Faber published a follow-up paper called 'Relative Strength Strategies for Investing' which introduced the concept of price momentum as a way to distinguish between strong and weak assets in the portfolio. That paper applied an intuitive method of capturing asset class momentum that involved averaging each asset's rate of change (ROC) across five lookback horizons, specifically 1, 3, 6, 9 and 12 months. By averaging across lookback horizons, this approach captures momentum at multiple periodicities, and also identifies acceleration by implicitly weighting near-term price moves more heavily than price moves at longer horizons.

In May of 2012 we published a whitepaper entitled, "Adaptive Asset Allocation: A Primer", a quantitative systematic methodology integrating the simple ROC based momentum concepts introduced in Faber's 'Relative Strength' paper with techniques derived from the portfolio optimization literature. Specifically, the paper explained how applying a minimum variance optimization overlay to a portfolio of high momentum assets serves to stabilize and strengthen both absolute and risk-adjusted portfolio performance.

Article Series

We are going to range far and wide in our exploration of global dynamic asset allocation. This article, the first in our series, will explore a variety of methods to rank assets based on price momentum. The second article will introduce several approaches to rank assets based on risk-adjusted momentum measures. The third article will introduce a framework for thinking about portfolio optimization, including several heuristic and formal optimization methods.

Our fourth article will discuss ways of combining the best facets of momentum with the best techniques for portfolio optimization to offer a coherent framework for global dynamic asset allocation. The objective here will be robustness and logical coherence rather than utilizing optimization for best in-sample simulation performance.

Lastly, we are considering introducing some ensemble concepts and adaptive frameworks as a cherry on top, but we aren't sure how far we want to go yet, so we'll just get started and see where it takes us.

The following illustrates the proposed framework for this article series:


Click here to read the complete article at GestaltU.



Note : Here are some additional Advisor Perspectives articles by the Butler-Philbrick-Gordillo team:


Adam Butler and Mike Philbrick are Portfolio Managers with Butler|Philbrick|Gordillo & Associates at Macquarie Private Wealth in Toronto, Canada.

© Butler|Philbrick|Gordillo & Associates, 2013

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