It was last week that we sent out our end of year recap of how managed futures had fared over the past 12 months. Bypassing the idea of doing a program by program breakdown in favor of strategy performance analysis, we found ourselves facing a common question- how, exactly, should these programs be classified?
We eventually settled on a fairly conventional approach to strategy categorization- guided by the elements that drive the performance of a program- and while these categories are certainly helpful when trying to understand the general performance of various strategies, when it comes down to evaluating individual programs and making decisions about your portfolio, it may not be the most elucidating method of strategy division. Let us explain…
Anyone who has ever had to conduct due diligence research on a host of managed futures programs will likely tell you the same thing: the traditional labels we apply to these programs are rarely a perfect fit. Part of this might be attributed to the evolution of strategy development for CTAs as a whole. As managers have attempted to enhance their opportunities for profit and better manage their risk exposure, various elements of strategy have melded into a host of hybrid programs that are not so easily sorted into distinct piles.
For instance, the Rosetta program is the poster child for defiance of conventional managed futures categories. Their fundamental trading style intuitively places them in the discretionary trader category, and yet they are incredibly distinct from, say, a Dighton Capital. They also engage in complex spread trading strategies, and specializing in agricultural trading, but their discretionary approach makes them very different from systematic agricultural trading program Global Ag, and even more different from the hybrid spread trading program we see with Emil Van Essen. In this light, effectively categorizing these programs under traditional labels becomes exceedingly difficult.
For the organizational nutcases among us, the intuitive response is to develop some sort of strategy category hierarchy- a road map of reflective questions that ultimately spits out a very specific, final categorization. Even this approach, as appealing as it seems in theory, falls victim to a logical fallacy, insofar as it assumes that these categories are mutually exclusive, which is the only way that a branching categorization system works.
For some, the category conundrum may seem silly. At a certain point, you have to wonder, Why bother with sorting through the details at all? Why not compare the programs based on performance and risk metrics alone? Why not simply group the programs by their correlation levels?
You’re talking to a group of huge statistic junkies. We aren’t going to tell you that performance, risk and correlation aren’t important considerations when constructing a managed futures portfolio, because believe in their significance. However, just as these figures, in and of themselves, cannot paint a complete picture of a managed futures program, the numbers can fall short of helping investors really understand what, exactly, they’re investing in. Numbers may construct a vivid picture for the John Nashes and Matrix hackers of the world, but for most, they fall woefully short of establishing a clear explanation of behaviors and philosophies.
Perhaps more importantly, in a world of wild variance in track record length, assets under management and manager experience amongst the various managed futures programs, these data points cannot paint the panorama view of the managed futures landscape. Categorization provides an equalizer that is not dependent upon anything other than the defined mechanisms of trading associated with a given program. As such, an understanding of the strategic categories underpinning these programs can provide the context that connects the dots in a way that nothing else can.
Proper categorization can provide valuable perspective for investors and portfolio advisors alike, but the industry’s attempts to batch up the entire universe of managed futures programs into neatly defined categories just doesn’t seem as effective they could be. After countless hours white-boarding out the issues, crunching the numbers, and writing and rewriting this piece, we finally realized what the solution was… in the most absurd of analogies.
A Relational Perspective on Program Categorization
Those involved in the managed futures space will tell you that advisers and CTAs don’t really sell managed futures. The asset class doesn’t fit into supermarket-style aisles of options (though, really- are supermarket aisles ever perfectly arranged, either?). Applying that kind of retail taxonomy to a process that only vaguely resembles the business models historically associated with selling is a mismatch of sorts.
No, advisers and CTAs don’t sell to clients- they court them. We are the matchmakers, and our clients and managers are the potential lovebirds.
Stay with us, now.
Every investor is unique- they come with their own combination of prior investing experience, risk capital, risk appetite and tolerance levels, and understanding of portfolio construction. Sure- similar levels may result in similar investors, but no two clients are going to be exactly alike. In the same vein, managed futures programs are all unique as well. Sure- they may share common characteristics that make them easier to comprehend, but at the end of the day, the reason new programs are developed every year is because there will always be slight differences in how these characteristics are arranged. When you look at things from this angle, the matching of investors with managed futures programs requires a more nuanced understanding of personality composition than it does pitching a sale.
Now, admittedly, matters of the heart aren’t exactly black and white. Opposites can attract. Cultural divides can be bridged. Age gaps can be irrelevant… unless you’re Demi and Ashton. While investing certainly has its grey areas, we wouldn’t go so far as to say that this matchmaking analogy is perfect. We all know someone who just has a knack for setting up matches, often guided by intuition. Here, it’s not enough to have a “hunch” that an investor will hit it off with an individual program- you have to “psychoanalyze,” if you will, the compatibility of the two. This point is furthered when you think about managed futures categorization in the context of personalities. We’re not aware of anyone who requires a Myers-Briggs examination of their dates prior to dinner (and would be creeped out if we did), but by seeking to categorize managed futures programs, we essentially do just that… and it’s anything but creepy here.
For context, the Myers-Briggs assessment is a psychometric personality test that evaluates an individual’s association within four characteristic pools based on established dichotomies related to attitudinal, functional and lifestyle determinations. Based on the realm of possible combinations, the test outlines 16 different personality types. There may be variations within each four-characteristic combination, but the idea is to provide a general overview of a specific grouping of qualities.
In our mind, it’s high time that managed futures developed a Myers-Briggs test of their own.
If you look at a managed futures program’s strategy as its personality- or grouping of characteristics- the methodology of categorization- and investor analysis- shifts dramatically. It’s no longer just about including a spread trader in your portfolio or wanting some ag exposure; it’s about finding a program that most closely matches an investor’s risk tolerance, trading preferences and diversification on a totally different level. We won’t go as far as to we’re trying to be the Myers-Briggs of our space… but then again, maybe we will.
Introducing- the Attain Capital Program Category Assessment– or PCA.
While the differences between managed futures programs may be widespread and difficult to smash into a preconceived hierarchy of categories, the ways in which these programs can differ are more easily outlined. Based on our thousands of pages and hours of due diligence research, the major areas of distinction that we note are as follows:
Let’s break it down:
- What They Trade- What kind of contracts is the program trading? Are they generally constraining themselves to outright futures trading, or are they participating in options trading? Does their program trade both kinds of contracts? If none of the above, the program likely does not qualify as a managed futures program. This element is an important consideration, as different contract structure participation can carry unique risk profiles.
- Where They Trade-What markets does the program participate in? Do they, like a Cervino Capital Gold Covered Call Program, only trade one market? Are they focusing on a given sector, as stock index traders such as Paskewitz do? Have they built their program around a set of select sectors, like Rosetta’s trading of grains, softs and meats? Maybe, like Clarke Capital Worldwide, the program participates in a wide array of sectors. This characteristic is an important one for investors to consider. On one hand, focus on a single market or sector, particularly when traders rely on fundamental or discretionary signals, can play a significant role in the ability of a program to succeed, whereas diversification of market exposure may help other programs hedge against one trend wiping out the positions of an entire program.
- How They Trade- If we know what contracts are being traded in which markets, the next obvious question is what the guiding philosophy behind the trades might be. The most common classification here is that of trend following or momentum trading, where a manager will attempt to latch on to the momentum of an emerging trade in order to capitalize on the price movements therein; these are the more traditional managed futures programs. Another strategy might be mean reversion. Call it contrarian or counter-trend if you will; this strategy bets that the trend will reverse. The medium between these two would be a relative value strategy, where positions are offset in such a way that they culminate in neutral market exposure- a strategy that some might include spread trading under. A program that doesn’t quite fit within these strategies may be using a hybrid of these perspectives, such as a program embracing a variety of trading models. This distinction can be indicative of the amount of risk taken on by a manager, and the volatility of a program in general.
- Why They Trade-What makes a program place a trade? Is it a systematic signal, such as a breakout from a moving average? Is it a fundamental signal, such as a report on industrial demand for copper? Is it a blend of the two, where the manager executes their discretion by interpreting a variety of signals in order to gauge the prudence of a given trade? Maybe the program is a hybrid of these ideas, with a discretionary overlay when it comes to a specific sector, and pure systematic reliance in another. The why provides an element of predictability- not necessarily in performance, but in process- that may appeal to investors of varying risk appetites.
- When They Trade- Speaking of timing… this may be the more complex elements of categorizing managed futures programs, as the interpretation of the brightlines dividing their meaning may change depending on who you talk to. On our side of things, we want to know if a program looks to get in and out of trade within a one day period, a 2 to 7 day period, or longer. It’s entirely possible that a program will have a collection of models that trade on different timeframe levels. This element of evaluation can be incredibly important to understanding how a program works, as different timeframe guidelines for trades may perform differently under specific market circumstances.
That’s great… now how do I use it?
As we played around with the various combinations of characteristics outlined here, we found the descriptions they provided us with wound up being pretty accurate. This was a bonus… until we started to do a “strategy breakdown” following these lines in the sand; at that point, we were functionally were back to doing program by program reviews. That’s not necessarily a bad thing, but for functional purposes, it made the relational approach to categorization a little unreasonable for instances where you’re trying to look at things from 20,000 feet. In fact, using this methodology, there are 764 different category profiles in the managed futures space- enough to make Myers and Briggs insanely jealous and drive the average investor crazy.
The relational approach to program categorization may not be useful to those doing big picture industry analysis, but its specificity can be of great use to the individual investor when it comes to understanding the differences between programs available and figuring out which are best suited for inclusion in their portfolio. In essence, the relational approach serves as a framework for evaluation of a program’s makeup; a 3D view of its composition and ideology. It basically provides a compatibility assessment for an investing relationship, forcing the investor to look behind the impressive physique of a program’s performance and the age of the track record to what lies within.
Now, just as we would never advise making a major relationship decision based on the outcome of the Myers-Briggs assessment alone (again, creepy- and are we really supposed to believe there’s only 16 kinds of people out there?), the relational approach outlined here is not the end-all, be-all for managed futures program selection. It’s just one piece of the puzzle, and is ultimately most helpful when used in conjunction with evaluation of past performance, various risk metrics, non-strategy related program attributes (assets under management, track record length, etc.), and the qualitative due diligence that dedicated IBs like Attain can provide. We understand how these pieces work together, and, further, that the road to allocation is a long and complicated one. That’s why we’ve invested so heavily into creating tools that make that journey a little more comfortable for the wary investor. In our experience, when you see the full picture- well, that’s when the magic begins. That kind of self-awareness and general understanding of the field in which you’re operating, in our minds, is a match made in heaven (sorry, couldn’t help ourselves).