Tactical Adaptive Innovation Strategy Whitepaper

July 22, 2019

There are few of us who have not, at one time or another during our investing career, wished we had the foresight to invest in the up and coming companies which turned into large and successful companies while turning the world on its head with innovation. Aside from the financial rewards, which can be large, investing in leading edge companies brings a feeling of participating in something big and important.

The challenge of investing at the leading edge has always been in selecting the technologies and companies in which to invest as well as the substantial risk of investing in companies which failed in their quest either through impractical ideas or poor management. However, innovation will continue in virtually any economic scenario you can envision!

The Tactical Adaptive Innovation Strategy provides our subscribers with a way to invest in leading edge technologies while significantly lowering the risks. 

Innovation Defined

In today’s rapidly changing world, innovation cuts a wide swath including big data & analytics, nanotechnology, medicine, networks, genomics, energy & environment, robotics, 3-D printing, bioinformatics, and financial services. These sectors are known for high growth and high returns but also come with very high volatility. 

The Tactical Adaptive Innovation Strategy brings three tools to bear which deliver much of the potential return while limiting the volatility.

  • A very unique fund basket
  • Our Market Conditions Model
  • Our Tactical Model with Adaptive Dynamic Momentum

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 Basket Of Innovations

Back in 2014, I took note when four new Exchange Traded Funds were introduced called the ARK Innovation Funds. Of course, being new, they had no track record and while the funds’ holdings were intriguing, I was not prepared to stick my toe in the water.

Fast forward to 2019, when I began developing the Tactical Adaptive Innovation Strategy. ARK Innovation funds had become well-established funds with a focused research team, several billion in assets under management, and five years of successful history. I put them on my list of candidates along with several dozen other established ETFs which lay claim to investing in innovation. 

I started with the strategy concept, roughly three dozen funds, and our Tactical Model which is capable of crunching dozens of funds to identify those which outperform. Two things became clear:

  • The ARK Innovation funds deliver relatively higher performance than other candidate funds
  • The risk levels are on the high side for conservative investors 

ARK Innovation Funds 

A paragraph on the ARK website describes a scope of investing which I found to be very closely aligned with my strategy goals:

Investing in the future, today. ARK defines disruptive innovation as the introduction of a technologically enabled new product or service that has the potential to change an industry landscape by creating simplicity and accessibility while driving down costs. ARK ETFs aim to provide access to companies benefiting from disruptive innovation.

ARK Innovation funds are actively managed and are based on company-specific stock picking. I spent quite a bit of time reading the ARK investment materials and watching their Webinars. It is clear that the ARK management and research team is extremely capable and enjoys working together. I was impressed with this response to an investor question regarding stock timing for buying and selling companies:

“Yes, so the ARK investment horizon is 5 years for all actively managed strategies. For entering, we are valuing the company and setting a 5 year price target for each company. We are looking for the compound of this; we’re looking for a doubling of the stock. For exits, if a stock drops below the 15% hurdle, it could potentially be a candidate for replacement in one of the strategies. This valuation one of the six scores we assess for each company. Four other scores we assess are People Management and Culture, Moat and Barriers to Entry, Execution, and Product and Service Leadership. We assign a score to for each of these to the individual company. The last score we assign is our thesis on Risk, including geopolitical or regulatory risk. Those altogether are what drives our positioning within the portfolio. Usually it's the Valuation score which changes day over day.”

Speaking of long term success, I have a strong preference for building strategies which have withstood a full market cycle. However, innovation style ETFs are a relatively recent creation and history is limited. Believing that the opportunities were significant, I decided to work with five years of history and use our Tactical Model and Market Conditions Model to ameliorate the risks.

While each of the five ARK actively managed ETFs focuses on a specific sector, there is considerable overlap among the funds. The financial services innovation fund is too new to include in the Strategy. I plan to review the basket annually and may adjust the criteria to permit phasing in of newer funds. The goal is to capture as much innovation and as little risk as possible.

This is how my basket of innovation ETFs performed using an equal weighted Buy and Hold strategy:

Clearly, a rather nice Compound Annual Growth Rate, but the drawdowns are excessive without factoring in steeper possible drawdowns during a bear market for which I have no data.

Reducing The Bear Market Risk

My first thought was to mitigate, to the degree possible, the bear market unknowns. The easiest way to accomplish that was to use the Market Conditions Model (see What Is A Market Conditions Model? How Does It Lower Risk?) to identify the Hostile market conditions which pose the greatest risk. Since we need something in which to invest during Hostile market conditions, I selected Treasury ETFs which generally do well under Hostile conditions.

Identifying The Trend

Our final fund basket consists of 3 innovation ETFs and 2 Treasury ETFs. The Tactical Model can select any of the five (or cash) during Balanced and Favorable market conditions and Treasury ETFs (or cash) during Hostile market conditions.

The innovation ETFs are first and foremost growth stocks synonymous with rapid appreciation and high volatility. Successful trend identification for these ETFs requires the ability to recognize and hold positions on established strength. However, high returns can be quickly lost with large drawdowns. (The paper on Full Market Cycles goes into more depth on this subject.) Suffice it to say that signs of structural weakness in prices must be acted upon quickly.

Adaptive Dynamic Momentum, the trend identification methodology used by our Tactical Model, provides the critical pathway to finding (and sticking with) winners while avoiding (and/or quickly discarding) losers. During the development process, the Tactical Model identified an exceptionally long average primary trend length. While Adaptive Global uses an average primary trend length1 of 24 weeks, and Adaptive Income uses an average primary trend length1 of 6 weeks, Adaptive Innovation uses an average primary trend length1 of 31 weeks.

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

The inclusion of Treasury ETFs not only provides a haven during Hostile market conditions but low-risk alternatives when the innovation ETFs are catching their breath or performing poorly.

The Innovation Strategy selects the 2 best performing eligible ETFs (or cash).

It also employs volatility weighting which allocates inversely to volatility. Given the selection of 2 innovation ETFs, the highest weighting will go to the one with the lowest volatility which tends to reduce drawdowns. Given the selection of 1 innovation ETF and 1 Treasury, the lower volatility Treasury ETF will receive the highest weight which, however, is capped.

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. Holding periods for the Adaptive Innovation Strategy tend to be quite long for a tactical strategy.

Scoring The Results

While we have history going back to the fall of 2014, our Tactical Model is not fully “warmed up” until October 2015. We calculate Compound Annual Growth Rate (CAGR), Maximum Monthly and Daily Drawdown, and a host of other statistics from October 2015.

While we don’t have the benefit of examining performance during a full market cycle; we have been through 3 significant corrections (Feb 2016, March 2018, May 2019) and a quick bear market (December 2018).

Compared with buying and holding equally weighted innovation ETFs, we have increased CAGR slightly and cut MaxMD by nearly 40%. 

-This chart compares the Tactical Adaptive Innovation Strategy to the S&P 500:

During the test period, SPY turned in a CAGR of 14.3% (versus 31.3% for Innovation) and a MaxMD of 13.5% (versus 12.3% for Innovation)

Conclusion

If you've ever been tempted to dip your investment toe into the leading edges of innovation but were put off but the high volatility; the Tactical Adaptive Innovation Strategy may just fit the bill for a "big toe" portion of your portfolio.

The Adaptive Innovation Strategy smoothly and effectively transitions between risk on and risk off while delivering exceptional returns. It provides exposure to those parts of the economy which tend to lead economic growth and deliver premium returns. Further, innovation is built into our market economy and is likely to continue no matter the state of the economy, monetary, or fiscal policy.

Adaptive Innovation combines the use of actively managed ETFs with an active tactical 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. 

There are also good reasons to keep an allocation modest:

  • The innovation space is inherently volatile.
  • We lack the benefit of historical performance for a full market cycle. 

Conservative investors should consider Adaptive Innovation for no more than 5% to 10% of a portfolio. 

One interesting approach is to pair Adaptive Innovation with the Adaptive Income Strategy. For the period October 2015 through June 2019, blending a 75% allocation to Adaptive Income (8.5% CAGR and 2.8% MaxMD) with a 25% allocation to Adaptive Innovation (31.3% CAGR and 12.2% MaxMD) would have worked out to a blended CAGR of 14.2% and MaxMD of 5.2%.