Who we are

The AQL DARE founders team are three leaders in their respective areas who have collaborated for many years and share a common vision that the investment industry can and should do more for investors. They also share both deep experience and a mindset of innovation—the very combination needed to bring investors a better way.

David M. Anderson

AQL was originally founded by David M. Anderson to develop innovative solutions for the all-important asset allocation decision at the heart of every investment portfolio. We think it’s fair to describe David as a legendary figure in the investment industry. Before founding AQL, he was a key early developer of investment management in futures and options and a pioneer in the development of alternative investment products. He accomplished much of the above as a founder of various investment businesses in association with what is today the Man Group, one of the most successful hedge funds in the world. David was vice chairman of the London Commodity Exchange, and as director of the Securities and Investments Board, he oversaw the implementation of the UK Financial Services Act.

As an investment innovator at many levels, David has witnessed the best, the worst, and—as he puts it—the vast middle ground of mediocre results in an industry that drives clients toward ineffective asset allocation and charges a lot for, ultimately, a little. David founded AQL to bring investors the value they deserve.

Jeffrey Farrington

Joining David Anderson in leadership at AQL is Jeffrey Farrington, AQL’s CEO, a former trader and treasury manager at the Man Group, managing director of the UK office of Machado Asset Management, co-founder of US-based Broadmark Asset Management, and a financial advisor for Merrill Lynch Global Wealth and Investment Management. Jeff has collaborated with David for three decades, and he brings complementary expertise to AQL in disciplines that matter deeply to investors including technical analysis, alternative-investment risk management, fund management, trading strategies, and client service. Jeff’s commitment to the advantages of dynamic asset allocation as a superior approach for investors is longstanding and traces its roots to his previous work with the Man Group. In 2020, Jeff joined with David Anderson and Don Smiley, AQL’s chief technology officer, to create a truly democratized approach to competitive returns with lower volatility—what we today call the AQL DARE portfolios.

Don Smiley

Completing the leadership team is Don Smiley, AQL’s CTO, who brings a rare combination of software engineering chops and investment industry experience. Don’s understanding of business processes combined with the engineering skills to implement them via AQL’s proprietary trading methodologies and infrastructure provide a groundbreaking opportunity for investors. Don is founder of Portalytics, a firm specializing in portfolio modeling; he was a co-founder along with AQL CEO Jeff Farrington of the registered investment advisor Broadmark Asset Management, where as director of research and CTO he developed the software for that firm’s selection strategies and trading systems; and he was director of research for McKinley Capital Management, where he developed that firm’s proprietary trading allocation automation. Don’s shared vision for the future of using systematic analysis and efficient trading protocols makes AQL DARE portfolios a breakthrough approach.

Deeper dive: What is wrong with the investment industry?

We will say it plainly: The approach used for clients across most of the investment industry today is based on errant logic.

Here’s why. More than a century ago, neoclassical economics, seen by many as potentially a true hard science, planted the seeds for “Modern Portfolio Theory” and its faith in the idea that asset values are driven by market efficiency, rational behavior, and the equilibrium of supply and demand. If true, all you need as an investor is to create a blend of likely risk, return, and correlation across multiple asset classes and then watch your “diversified” portfolio do its magic in protecting you.

But as we can all see with our own eyes, time after time, consumers, producers, investors, regulators, and others behave outside the bounds of what would be expected in an economic world governed by “efficiency,” “rationality,” and “equilibrium.”

In reality, economics is not a hard science—it is more like a person with a magnifying glass chasing 20 unruly puppies. You can see just what’s right in front of you while all around you everything changes, and very little of it is truly predictable.

Here’s why. More than a century ago, neoclassical economics, seen by many as potentially a true hard science, planted the seeds for “Modern Portfolio Theory” and its faith in the idea that asset values are driven by market efficiency, rational behavior, and the equilibrium of supply and demand. If true, all you need as an investor is to create a blend of likely risk, return, and correlation across multiple asset classes and then watch your “diversified” portfolio do its magic in protecting you.

But as we can all see with our own eyes, time after time, consumers, producers, investors, regulators, and others behave outside the bounds of what would be expected in an economic world governed by “efficiency,” “rationality,” and “equilibrium.”

In reality, economics is not a hard science—it is more like a person with a magnifying glass chasing 20 unruly puppies. You can see just what’s right in front of you while all around you everything changes, and very little of it is truly predictable.

Again and again, we see that it is not possible to predict the relative performance and correlations of multiple asset classes not only tomorrow but also weeks, months, or years (buy and hold!) in the future. This traditional way of allocating assets fails at both elite levels (such as hedge funds) and with widely available funds, and it fails whether holdings are determined actively through individual security selection or passively through index investing.

Here is the deep-down reason for the failure of traditional portfolio construction: The way assets are allocated depends on relationships among asset classes being essentially stable and predictable. But these relationships are often unstable and unpredictable—as in 2022 when the assumed low or negative correlation between equities and bonds broke down and they became positively correlated in a highly negative market. In other words, because of flawed assumptions, diversification failed when it was needed most.

For investors, traditional portfolios had one job, and they failed to do it—again.

If you could see just one day ahead, would it change how you invest?

At AQL, we fully realized a number of years ago why traditional asset allocation fails to protect investors: No matter how many white papers and fund quarterly reports were written to dissect every previous movement of asset classes, the future behavior of assets is not an echo of the past. The future is instead a living, dynamic, literally constantly evolving result of the actions that millions of consumers, employers, governments, investors, and others take every day in the present.

Despite what the traditional investment industry might imply, there is no certainty about what “will happen” in the economy or markets or between asset classes; there is only the constant motion of the players, all contributing every day with conclusions and behaviors that in aggregate affect the conclusions and behaviors of the next day, and so on each day.

Now, what if we all as investors could harness that motion in our portfolios?

AQL momentum-driven dynamic portfolios

AQL removes the notoriously unreliable predictions of Modern Portfolio Theory from the picture and instead lets price movements—which are largely persistent in the near term—tell the story.

In other words, to decide on asset allocation, we are analyzing price (transparent, objective), not what theoretically underlies price (murky, subjective).

It wasn’t possible as recently as a few years ago, but now, advances in the application of ensemble decision-making techniques developed in the field of artificial intelligence have allowed us to develop a quantitative momentum-driven strategy that analyzes price movements among asset classes each day—including cash, which is absolutely an advantageous asset at times—and effects portfolio responses that are tuned not to what anyone just expects to happen, but to what the markets are actually doing. The market (which really means, “human behavior”) is an amalgamation of individuals that may flip back and forth daily in optimism or pessimism about a given asset class. However, when enough investors move in the same direction, the price will be driven in that direction. This is the basis of price momentum.

AQL portfolios are not high-frequency trading vehicles that instantaneously dump and replace assets—because such rapid-fire trading, while it may have its benefits, does not capitalize on persistence in behavior, which is related to price movement. Instead, AQL builds a portfolio of efficient exchange-traded funds (ETFs) and potentially cash that is delineated into daily “slices”—then we use our ensemble of momentum-based algorithms to readjust only 1/21 of each portfolio (a little less than 5%) each trading day.

Let’s not depend on luck

We all occasionally have good luck in our investing timing and love when that happens. But while luck is a bonus, it is never a plan. And there is also that thing called “bad luck” when, for example, you move into an asset class soon before it begins to stagnate or tank.

With AQL portfolios, we purposefully reduce timing influence by distributing trading signals and position adjustments across all the trading days of the month, as described above. So, with AQL, investors are not likely to win the lottery (a.k.a. perfectly time a price spike with a large buy) but will, as compensation, greatly reduce the possibility of a particularly damaging bit of mistiming.

The AQL methodology not only reduces “timing luck” and gives investors a purer play on momentum—it also creates a smoother return path. By adapting to market dynamics and addressing volatility and losses in a timely, systematic manner, AQL portfolios can increase the effect of compounding, which is very powerful but requires gains (naturally!) to compound.

AQL portfolio performance

With a dynamic strategy that harnesses human behavioral patterns, will an AQL portfolio sometimes be behind the curve and therefore underperform the relevant benchmark in a given day, week, month, or other period? Yes, of course—but likely not for the long run.

While no methodology, ours included, anticipates what will happen with 100% accuracy, AQL strategies bring a new level of precision and efficiency to detecting and responding to price movement among asset classes probabilistically, and they will tend to incrementally adjust in a timely manner when they are behind.

Our approach to capturing momentum in the markets can greatly reduce the frequent bouts of underperformance during periods of heightened volatility that plague the vast majority of actively managed portfolios…while having a very good chance of earning more than the relevant benchmark over time.

Seeking to increase risk-adjusted returns

Investors have varying goals but generally have a shared performance goal of achieving the best possible return for the level of risk they take. AQL DARE portfolios have the same goal, so we combine individual strategies implemented on a pro-rata basis over the trading days of a month. In this way, we dynamically diversify across asset classes, strategies, and time.

AQL Portfolios

Portfolio

AQL DARE 50/50

AQL Bold Time Diversified

AQL Hybrid Time Diversified

Vanguard Balanced Index Inv
(Benchmark; 60 stock/40 bond)

Vanguard Balanced Index Inv (Benchmark; 60 stock/40 bond)

(1) Based on 1-year rolling returns, 12/92-12/23
(2) 12/92-12/23; for AQL portfolios, backtested
(3) A measure of return vs. downside volatility; higher number = higher risk-adjusted return (4) Benchmark; 60 stock/40 bond