Here's our monthly sneak peek at March hedge fund and managed futures returns from Kettera Hydra Platform Investor Letter.

Kettera Hydra platform gives qualified investors the ability to access top-tier fully vetted macro, managed futures, FX and hedge fund managers at lower investment minimums and the same fee structure as direct managed accounts. 

The platform separates the "wheat from the chaff" and only lists best-in-class managers. Kettera conducts rigorous due diligence on each manager before a manager is approved on the platform.

Hedge Fund Strategy Insights

#1 In February, long convexity and relative value volatility strategies weathered the turmoil well. In March they exceeded all expectations.  Many of the programs, both on Hydra and off, posted the best month since their inception. Simply put, most of these strategies focus on volatility relating to the equities markets, and the equities markets served up a lot of it in March. 

#2 Discretionary commodities managers also generally excelled during the month.  Those focused on energy and other industrial commodities, primarily base metals, appeared to call the collapse in both correctly during the month.  The more profitable ag traders – particularly relative value and spread traders – benefitted from demand destruction and short positioning in corn, in particular.  Overall, however, discretionary ag specialists had mixed results as corn and soybeans fell while other products rallied. 

#3 Many discretionary global macro strategies redeemed themselves as fundamental factors that began building in late January, or earlier, blew up and accelerated profits in multiple themes. The more successful programs were short base metals and energy, as Chinese demand was destroyed, and long U.S. fixed income. A fortunate few even caught the “up-down” U.S. dollar moves – the sell-off then ensuing mid-month rally.  Quant (or model-driven) macro managers seemed to be less successful on the whole, especially in the equities markets, but many fundamental models still caught many of these moves. Some quant strategies also benefitted from long volatility positions. Overall the quants’ results were mixed, with single-digit gains or losses on the month.

#4 Systematic trend programs once again appeared to offer a mixed bag.  Most of the managers we track tended to post positive returns, mostly in the fixed income, short term rates, and energy sectors.  The equities markets seemed to offer the most challenges across the board, as lingering long positions were stopped out for losses in the first few days of the month.  The deciding factor in March as to whether a price-based trend follower was profitable seemed to rest on whether it had an overweighting to short energy and commodities markets, able to get flat (or short) equities quickly enough, or long positions in fixed income and rates. 

#5 Short-term and higher-frequency programs once gain generated mixed to net positive returns, given the expanding volatility and quick turnarounds in March in several markets. The markets definitely favored the higher frequency players – particularly those with breakout models (as opposed to mean-reverting systems, much less profitable).  Programs with slightly longer holding periods tended to get caught on the wrong side of switchbacks.   For most short-term programs, short energy and base metals markets, equities and long VIX volatility positions ruled the day, whereas other sectors such as FX and agricultural grains tended to be less lucrative.

#6 Equities strategies performed badly overall, unsurprisingly, with most returns being even worse than February. Probably the best of the bunch were equity market neutral strategies, where gains in short positions mostly “neutralized” the losses on longs. Most equity long-short managers strategies seemed to suffer from their long-beta biases, for which this style is notorious.  (We opine that one reason numbers for this group were not worse was that February had stripped them of many longs.)  And, of course, long bias and long only strategies had nowhere to hide, regardless of their sector of focus. Event-driven programs seemed to suffer greatly as they faced ever-widening spreads and more directional positions moved down; the subset of merger arbitrage strategies watched as entire portfolios of deals broke at once.

#7 Most of the artificial intelligence (AI) and machine learning-based strategies we track didn’t perform well in March. But this may make intuitive sense given how they function: These models are fed enormous amounts of data, looking for recurring patterns and relationships, and then try to “learn” which patterns can apply to current conditions and position things accordingly. When an unprecedented event occurs with unusual speed, with somewhat unprecedented reactions and remedies, the historical data offers nothing instructive.  We note that we didn’t see huge losses, and all strategies easily outperformed the equities markets, but the AI and machine learning programs were still generally negative on the month. 

Breakdown of March Hedge Fund Returns