Tactical Adaptive Global Strategy Whitepaper

July 25, 2019

The Tactical Adaptive Global Strategy is our flagship strategy. It provides the self-directed investor with hard-to-beat returns and exceptionally low investment risk across a blended portfolio of global equities, fixed income, commodities, and precious metals.

Measured across a full market cycle October 2007 through June 2019, Adaptive Global shows the following approximate percentages invested across major asset classes:

  • Equities 51%
  • Fixed income 31%
  • Real Estate 7%
  • Precious metals & commodities 9%
  • Cash 2%

Historical, backtested performance for this full cycle shows a Compound Annual Growth Rate (CAGR) exceeding 15% and a Maximum Monthly Drawdown (MaxMD) of less than 9%.

Before moving on, let's set the stage with an explanation of Tactical Asset Allocation.

Tactical Asset Allocation

Tactical Asset Allocation (TAA) is among the best investment tools available for navigating Full Market Cycles. While TAA tends to lag in late bull markets, it offers opportunities for higher Compound Annual Growth Rates and lower Maximum Drawdowns across a full bull/bear market cycle. Among the greatest strengths of TAA is its mechanical, rules-based approach, which not only keeps the portfolio attuned with market conditions but reduces the anxiety of managing the portfolio.

Perhaps the single biggest distinction between Tactical Asset Allocation and Modern Portfolio Theory is that while Modern Portfolio Theory seeks to reduce risk by spreading it across several asset classes, Tactical Asset Allocation seeks to reduce risk by cutting it.

Please see What Is Tactical Asset Allocation? How Does It Improve Returns? for a more complete discussion of Tactical Asset Allocation.

Building A Global Fund Basket

The foundation of Adaptive Global is a basket of low-cost, passively managed, index Exchange Traded Funds (ETFs). It is our Market Conditions Model and Tactical Model which turn this basket into a dynamic, actively managed investment strategy.

Tactical Asset Allocation strategies generally use a basket of 5 to 10 funds; however we use a much larger basket for improved global and asset class coverage. I maintain a funds database of nearly 400 funds, most of which have been gone through a “tryout” process for inclusion in the basket. 24 funds have made the cut:

  • 9 domestic equity index funds including large, medium and small caps
  • 1 domestic real estate fund
  • 4 international equity index funds covering Europe, Asia, and Emerging Markets
  • 1 international real estate fund
  • 6 US Treasury funds from short to long duration
  • 1 domestic investment grade bond fund
  • 1 broad commodity fund (grains, energy, metals, and precious metals)
  • 1 precious metals fund

Notable for their absence are international bond funds, none of which carried its weight when added to the fund basket and few of which have the required history. 

One of the requirements for ETFs used in Adaptive Global is that the ETF history must cover a full market cycle back to October 2007. While it is possible to infill history using similar Open End Funds with longer histories, I did not feel comfortable using substitutes.

Market Conditions

A large basket also allows us to tailor fund selections to market conditions. For example, we don’t want to be invested in short term Treasuries in a rip roaring bull market nor do we want to be invested in emerging market equities during a bear market.

The Market Conditions Model (see What Is A Market Conditions Model? How Does It Lower Risk?) is a multi-factor model that tracks price momentum, credit risk, market valuation and analyzes the interrelationships of these factors to identify periods of high and low directional probability. The Model identifies three market conditions:

  • Favorable: A strongly trending market with little risk of major decline. Unexpected declines are likely to be temporary and relatively short-lived.
  • Balanced: Risks of market decline and opportunity for advance are roughly equal; however conditions are supportive of increased volatility and uncertainty.
  • Hostile: High risk of extended market Correction (10%+) and Bear Market (20%+) declines and large equity drawdowns.

The Model measures market conditions in a probabilistic way. For example, it may signal Favorable conditions if there is a high probability of a market rise with low risk. However, a signal of Favorable conditions is not a guarantee of a Bull Market nor does a signal of Hostile conditions presage, with certainty, a Bear Market. However, the three conditions, when coupled with the appropriate fund baskets, work incredibly well in lowering risk and improving returns across full market cycles.

The Adaptive Global fund basket is further tailored to current market conditions:

  • Favorable: The fund basket emphasizes domestic and international equities supplemented with real estate, commodities and fixed income.
  • Balanced: The fund basket includes a mix of larger domestic and international equity funds together with a complement of high quality fixed income.
  • Hostile: The fund basket emphasizes a broad spectrum of government fixed income together with a limited selection of large cap equity funds and commodities.

Identifying The Trend

Four years of research and development went into Adaptive Dynamic Momentum (see Adaptive Dynamic Momentum: Improving Trend Identification), our ranking algorithm. While most tactical ranking is performed using fixed length periods; Adaptive Dynamic Momentum identifies the optimum ranking criteria for each fund, each week. 

Adaptive Dynamic Momentum is used by our Tactical Model to provide the critical pathway to finding (and sticking with) winners while avoiding (and/or quickly discarding) losers. During the development process, the Tactical Model identified the ideal average primary trend length1 of 24 weeks.

Fund ranking is just the beginning of the process for selecting funds for the next rebalance. We are just as interested in how well a fund is likely to continue performing in the future as how well it has performed in the past. Adaptive Dynamic Momentum assigns a confidence level to each fund's trend ranking. We use the combined ranking and confidence level to make the final selections.

1 The optimum primary trend length identified by the Tactical Model varies by fund by week across a broad range of possible lengths so the “average” is not indicative of the actual primary trend length used for any individual fund or week. For example, Fund A may have a primary trend length of 17 for the same week in which Fund B has a primary trend length of 4, Fund C has a primary trend length of 9, and so on. The Tactical Model also identifies and applies a secondary trend length by fund by week. It is the combination of the primary and secondary trends, together with some additional filtering, which ultimately determine the Final TrendScore for each fund each week.

Allocating Funds

Once the funds eligible for the next rebalance are selected, portfolio weights are assigned to each fund. We employ volatility weighting algorithms which allocates larger percentages to funds with low volatility and smaller percentages to funds with high volatility. The small decrease in return is offset with a larger decrease in portfolio volatility.

Adaptive Global spreads the allocation across the best 3-5 funds for diversification. The number of funds used depends upon the market condition with Favorable conditions warranting a more focused allocation while Balanced and Hostile conditions employ greater diversification.

One of the newest features in our Tactical Model reduces the number of trades. Before replacing an existing position with a higher trend scoring fund, the Model checks to see if can hold the existing position without compromising expected performance. For the Adaptive Income Strategy, this reduces trades by 6% while extending the average holding period for some funds by as much as 18% providing more opportunity for favorable tax treatment.

Scoring The Results

The Tactical Model is run full market cycle beginning October 2007 to calculate Compound Annual Growth Rate (CAGR), Maximum Monthly and Daily Drawdown, and a number of other statistics including monthly and annual returns.

The benefit of looking at the full cycle is the perspective on equity bear market performance. This shows that the Adaptive Global Strategy performed well during the 2007-2009 bear market and on its rebound. For another perspective, we examine statistics for the past 5 and 3 years:

  • 5 years: 8.3% CAGR, 6.0% MaxMD, and 191% Up/Down Ratio
  • 3 years: 9.6% CAGR, 5.7% MaxMD, and 200% Up/Down Ratio

By way of benchmarking the full market cycle, the Vanguard Balanced Index Fund, which invests 60% in equities and 40% in investment grade bonds, shows a CAGR of 6.7% and a MaxMD of 32.6%.

Withdrawals

The statistical summary suggests a Sustainable Withdrawal Rate of 9.5%. How is this calculated?

  1. Assume that the Maximum Monthly Drawdown (8.7%) occurs on the day that investment in the strategy takes place. That leaves 91.3%.
  2. Multiply 91.3% by the CAGR of 15.6% leaving a CAGR of 14.2% on the original investment.
  3. Withdraw 2/3 of the CAGR which equals the Sustainable Withdrawal Rate of 9.5%. Leave the remaining 1/3 invested to cover inflation and a safety factor

The calculated Sustainable Withdrawal Rate is well above the yields on all of our funds. How is this possible? It is due to large capital gains, especially during the early stages of the bull market. While capital gains are great, we want to identify a rate which does not rely upon out sized capital gains. Running the Tactical Model with different withdrawal rates provides some additional insight:

  • 4% withdrawal rate: Investor starts with $100,000 and then withdraws 4.0% annually in equal monthly installments over the full market cycle. The $100,000 would have grown steadily to $371,636 in January 2018 and then declined to $341,483 in June of 2019. 
  • 5% withdrawal rate: Investor starts with $100,000 and then withdraws 5.0% annually in equal monthly installments over the full market cycle. The $100,000 would have grown steadily to $334,993 in January 2018 and then declined to $303,476 in June of 2019. 
  • 6% withdrawal rate: Investor starts with $100,000 and then withdraws 6.0% annually in equal monthly installments over the full market cycle. The $100,000 would have grown steadily to $301,960 in January 2018 and then declined to $269,694 in June of 2019. 

We also use the Tactical Model to calculate the Sustainable Withdrawal Rate using just the past 5 and 3 years:

  • 5 years: 5.2%
  • 3 years: 6.0%

This suggests that a withdrawal rate between 5% and 6% would have proven more sustainable than 9.5%. Why? Because the big gains from the early bull market are behind us and we have no way of knowing when the next bull market will begin. Further, one should not lose sight of the fact that returns during the next 10 years are unlikely to match those of the past 10.

When it comes to withdrawals, I strongly prefer a fixed monthly amount which levels the portfolio volatility risk. Those with RMDs can always adjust or supplement the final withdrawal to meet requirements.

Conclusion

The Adaptive Global Strategy smoothly and effectively transitions between risk on and risk off while delivering exceptional returns.

It combines the use of low-cost, passive index funds with an active management strategy to reduce losses and improve returns. There is a large body of academic research which is both substantive and compelling in making the case for the use of Tactical Asset Allocation to manage all or part of an investment portfolio. With a coming bear market in equities and increased volatility in credit markets, investors should consider using Adaptive Global for part of their portfolios to improve returns and reduce risks.