Adaptive Dynamic Momentum: Improving Trend Identification

Updated January 5, 2022

If Einstein had never discovered that E = mc2, we may have never unlocked the importance of the links between energy, the speed of light and mass.

If Louis Pasteur hadn’t experimented with bacteria in his lab to determine what caused disease, millions of lives would have been lost due to less-than-sanitary practices in medicine and other fields.

The concepts of gravity and evolution, the discovery of DNA, the invention of penicillin, and millions of other inventions and experiments have created a better, smarter, healthier and richer world.

Investors are not exempt from the processes of adaptation, evolution and discovery, and they, too, can continually benefit from major advances in Tactical Asset Allocation (see What Is Tactical Asset Allocation? How Does It Improve Returns?).

Asset Allocation

In about the fourth century, Rabbi Aha proposed the following rule for asset allocation: “One should always divide his wealth into three parts: a third in land, a third in merchandise, and a third ready to hand.”

Asset allocation took a great leap forward in 1952 when Professor Harry Markowitz derived the optimal rule for allocating wealth across risky assets in a static setting now referred to as Strategic Asset Allocation where the basic premise is to select, buy and hold a diversified basket of assets through full market cycles.

1966 ushered in a series of 3 cyclical equity bear markets coupled with a bear market in fixed income which lasted until 1981.

The large drawdowns associated with Strategic Asset Allocation (aka “Buy and Hold”) during this period focused interest on Tactical Asset Allocation where the basic premise is to select and own the best performing assets within a diversified basket; a process which requires more active management and more frequent rebalancing.

What Is Momentum?

Momentum is the empirically observed tendency for rising asset prices to rise further, and falling prices to keep falling. The concept of momentum is best explained by behavioral economics rather than classical economics. To put it simply, the human traits of greed and fear explain much of the reason why momentum is a persistent factor in the markets.

Table 1 was prepared from 23 years of annual data compiled by Callan, FTSE Russell, and S&P Dow Jones. It demonstrates the annual variation across 10 different assets from best (green) to worst (red). Note that some of the worst performers are also best performers and vice versa.

The next chart demonstrates the potential of capturing the returns from the 3 best performing asset classes each year starting with $1000 invested at the end of 1997. Aggregate Bond takes the low end at $3,175 and S&P 500 Growth takes the high end at $7,215. $1000 invested equally each year across all 10 classes would yield $5,747 while owning the Best 3 rises to an astronomical $72,235.

Capturing the full returns of the Best 3 each year is a pipe dream, however the chart does demonstrate the potential benefit from selecting the strongest and discarding the weakest.

In the case of our Tactical Asset Allocation strategies, we perform that task monthly so we have a much better chance of riding winners to improved performance not to mention reduced drawdowns from the losers.

Traditional Momentum Measures

There is a large body of published academic and commercial research on Tactical Asset Allocation. Much of that body of work is focused on measuring the rate of change over fixed length periods or even a weighted average of fixed length periods (for example 20 weeks or weighted averages of 1+4+13+26+52 weeks). The percent change is calculated and compared for each fund in a basket to determine those with the strongest momentum.

The Achilles Heel of this methodology is that it fails to recognize and accommodate the many reasons why cycle lengths tend to vary across asset classes, sub-classes, and even funds. Worse yet, the cycle lengths are selected either arbitrarily or based on optimization using the best results from past history.

Enter Adaptive Dynamic Momentum

I devoted 5 years of research and testing to create a far better measure of momentum. Adaptive Dynamic Momentum (ADM) calculates a wide range of regressions for each fund, each rebalance period, and uses the length which best fits current conditions. It then performs another set of calculations using a secondary length which is a derivative of the primary to check that the shorter term trend is in sync with the longer trend. It then normalizes the results for each fund member of the basket for comparison of both strength and confidence. In short, ADM allows for more accurate trend identification as well as a smoother equity curve.

What does this mean for investors? It adds up to improved returns, decreased drawdowns, and greater confidence.

The graph below compares our Adaptive Global Strategy using Adaptive Dynamic Momentum to the same strategy incorporating traditional fixed length momentum using a weighted average of 1+4+13+26+52 weeks.

Adaptive Dynamic Momentum is impressively accurate in identifying the direction and degree of momentum in an investment trend as well as the probability that that trend will continue. No one wants to purchase a previously successful fund that proceeds to fall off a cliff.

It is important to note that Adaptive Dynamic Momentum is not a surefire cure for the doldrums experienced by tactical strategies when markets are experiencing a shift in trends. The true benefits of Tactical Asset Allocation are always measured across a full market cycle (see What Is A Full Market Cycle And Why Should I Care?). Regardless, Adaptive Dynamic Momentum steadily and repeatedly outperforms single and weighted period momentum across virtually every specialized and diversified basket of funds I’ve tested.

Why Adaptive Dynamic Momentum and Why Now?

Research shows that we are nearing the end of major market, fixed income, and credit cycles that began in 1981, some 40 years ago. The proximity of this shift creates urgency to improve upon tactical strategies, particularly trend identification. So too does the possibility that the Central Banks will drive more and more of the global debt structure into negative returns and/or pursue fiscal strategies which lead to currency debasement. In that case, something else will have to give, possibly asset prices and inflation.

We also have far more fund choices than were available during the previous cycle. Our fund baskets are more diversified, which makes adapting to shifts in domestic and international equities, fixed income, real estate and commodities markets that much more critical for investors.


Equity and fixed income markets continue to shift and change and will become even more challenging in the future. This demands that we adapt with new and improved technologies. Fortunately, the Adaptive Dynamic Momentum strategy for Tactical Asset Allocation is incredibly dynamic and adaptive to both today’s and tomorrow’s market cycles, representing a major improvement over previous algorithms. The development of Adaptive Dynamic Momentum has significantly raised the bar for portfolio performance using Tactical Asset Allocation.