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Managed Futures Make For Smoother Sailing

As the summer begins many of us try to head to the beach or out on the water. Boaters know all too well that given enough time on any body of water, unexpected conditions will arise, from the quick summer squall to a multi-day storm. This is also the way with markets/portfolios; it looks like all the signals are flashing risk-on, and some type of dislocation wallops the portfolio.

Boating and portfolio management have evolved. Old mariners’ sextants and fins have been replaced with sophisticated electronics and gyrostabilizers designed for safety and comfort. And liquid alternative strategies, one of the tools used by portfolio managers,  have evolved and can serve a key role in generating uncorrelated returns and helping to steady a portfolio in more difficult periods. Managed Futures, while a bit of a “catch-all” category, provides key benefits to both traditional and alternatives portfolios.

Some level of confusion on categorization of strategies, particularly those that are systematic rather than discretionary, exists, and thus, perhaps, makes investors wary. CTAs (Commodity Trading Advisors), quite often trend followers, seem to have developed a devoted following but the title was often used to describe all systematic strategies. Today’s preference for categorizing the strategies as Managed Futures, since they often use predominantly futures rather than cash securities for liquidity, is at least a step towards some standardization. Within Managed Futures, allocators have made more granular divisions using time frame, underlying asset, technology/math employed, or other functional titles. Confusing semantics aside, this group of strategies can each play a distinctive, uncorrelated role in many portfolios.

For simplicity here, the focus will be on all those non-discretionary, systematic strategies, which can fall under the managed futures banner, but which are distinct strategies. The best known of these is trend following, but this long-tenured strategy is only one of many and itself has many uncorrelated iterations. Here, lens’ can include speed, risk algorithms, underlying assets, and level of model sophistication. In concert with trend, it makes sense to employ shorter-term (hourly to weekly) trading strategies which often have momentum, break-out, and mean reversion sub-strategies. The newer technology is favored here as older systems have risk entrance and exit issues in today’s evolved market. To continue the marine comparison, think of the developments of boat electronics from clunky radar/sonar/loran to inexpensive, accurate, and integrated systems available on the smallest of vessels.

Global macro has long been used for its correlation benefit and return capture in dislocated markets. The systematic version fits nicely into the managed futures world and takes the information flow and reaction of a discretionary trader and codifies it. Taking the emotion out, and with advanced risk management, these programs tend to work well and often catch trades earlier than the discretionary versions. Some managers will have a portion of systematic embedded in the discretionary (usually no more than 25%) and this pairing provides a durable return stream.

Machine Learning/Artificial Intelligence is perhaps the systematic strategy that has captured the headlines and seems a natural evolution to human-coded more static algorithms. While the terms are thrown around a bit too loosely, perhaps in an attempt to garner AUM, utilizing the computer to learn has applications to both investment programs and the execution engine of those programs. In practice these programs generally arrive at different risk expressions than trend or short-term strategies. This lack of similar positioning is useful as allocators try to build out diversified and diversifying portfolios.

These examples are but a few of the classifications under the managed futures umbrella and the point is that depending on lens and granularity, an allocator can easily identify a dozen or more discernably different strategies. The natural question is how to utilize these strategies effectively as a stand-alone allocation, or more likely, in conjunction with other alternative or traditional (i.e., long-only) strategies. Given that this group of strategies are systematic, an allocator needs to lean more heavily on quantitative analyses of returns and exposures. Attempting to gauge performance on a forward-looking basis for any one manager can be quite difficult, even if the algorithms are provided, which usually is not the case. This propels the prudent allocator to use not one manager or strategy, but a thoughtful combination of several. Importantly, each should have a defined role to play and add value at the portfolio level while being uncorrelated to each other as much as possible. Creating this diversified return stream has the benefit of more stable performance and hopefully an all-weather return stream which has protective characteristics in a dislocation. This stops well short of a “tail-hedge” portfolio but should provide for a smoother ride when the seas inevitably become more challenging.

Jim Neumann is Partner and Chief Investment Officer at Sussex Partners


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