Singapore-based QuantEdge Global has been found sitting on top and at the bottom of the HSBC Hedge Weekly leader board for several years. The fund’s high watermark, up 44.94% year-to-date, has been the source of much discussion, with performance attribution reported to be centering on a “term premium” strategy. New analysis from Markov Processes International (MPI) attempts to explain the strategy that is identified on the HSBC platform as “Systematic.” After modeling the performance, Markov and his team ponder this categorization, pointing to a more nuanced macro global returns profile.

Quantedge Markov model performance
Markov’s proprietary modeling of Quantedge performance

QuantEdge isn’t shy about telling people to expect 30% volatility

The $1.3 billion QuantEdge Global fund has, as is clearly advertised, been a roller coaster of sorts. Its current significant performance is approaching double the fund’s annual average performance of 25.44%. Recent performance is among the high points in the funds history, which is currently sitting at the number two position on HSBC’s weekly performance tally.

The story in 2015, however, was different.

This is when the fund, with a clearly stated goal to target near 30% annualized volatility, delivered as promised, finishing 8th on the bottom 20 of the list, down -18.26% on the year. This drawdown might have been a good time to invest, assuming that QuantEdge is actually using managed futures CTA strategies that typically benefit from systematic cyclicality. Likewise the time to lighten up on the investment could have been 2014, when the fund finished the year up 29.25%, 20th on top performers list that year.

Just how did they do it? With a scattering of public information available, certain analysts are abuzz over the topic.

Markov asset class performance
This asset class performance relative to the fund’s performance is notable, particularly if it is a long short strategy

QuantEdge operates a relative value strategy and is impressive in consistently hitting volatility targets, even if they are high

QuantEdge’s innards may have been best revealed in a recent press report. A Wall Street Journal article, citing access to investor communications and comments from the fund manager questions, cited a “term premium” strategy along the yield curve. The fund sold short-term bonds, expecting short-term interest rates to rise, and bought long-term bonds, expecting long rates to stay the same or fall. The strategy works well during times of market distress.

With Friday’s strong employment numbers, the short end of the US bond market was up. Using a two-year yield as a proxy, it was positive by 9.21%, while the long end was up by less, 3.31% on the day, potentially benefiting the stated QuantEdge strategy.

Separate analysis would indicate that QuantEdge, if they have long / short exposure across the yield curve, is engaged in a relative value CTA strategy. Allocators might consider this strategy is correlated with the technical market environment of relative value price divergence and then mean reversion.

The concept behind the QuantEdge strategy is to build portfolios around specific risks, the Journal article pointed out. The notion is that the high risk premium yields both high win and loss size. This can be seen in the 30% volatility target that QuantEdge maintains. While many funds target volatility near the 10% or 15% level, here QuantEdge appears different not only do to the high level of the volatility, but the fact that they are on a reasonably consistent basis hitting their specific target.

Separate algorithmic analysis indicates the ability of a systematic strategy to accurately and consistently hit volatility and downside risk targets is considered a key factor in certain CTA programs. Volatility, which has been a traditional four letter word among equity investors, is now coming into vogue. The next step in portfolio management might be recognizing that when quality volatility is noncorrelated at the beta market performance driver level it can be combined with other consistent volatility sources to reduce overall volatility. But that concept is currently ahead of its time.

Markov contracting exposures
Markov’s work shows narrowing exposures with increased returns

Markov points to narrowing market exposure but rising returns

The QuantEdge strategy psychoanalysis only gets deeper when Michael Markov of Markov Processes International enters the equation.

Using the firm’s Dynamic Style Analysis (DSA) system, an outcropping of William Sharpe’s previous work in asset modeling, Markov uses a combination of indexes to replicate the 44.94% year to date performance, significantly ahead of the fund’s historical averages.

In a white paper titled “Like That 40% Return? Better Understand the Risks First,” Markov and report co-creator Daniel Li, PhD, modeled the strategy using general indexes. Their model pointed to six primary markets with two of them – three month US Treasury Bonds and Fixed income – as primary performance attribution. They used the Barclays US Treasury Long index, which is up 16.36% year to date. The three-month Treasury Yields ended 2015 at 0.16% and are currently trading at 0.28%, representing near a 43% year-to-date gain in yield, which translates into lower treasury prices by a similar ratio.

Looking at Markov’s modeling, the performance exposures narrowed over time but the returns, particularly in 2016, have increased dramatically. The portfolio constituents and weightings in their model were adjusted over the course of the study, but the formula for determining this exposure was not provided to ValueWalk and it is unknown if these adjustments were discretionary or systematic in nature.

This raises questions regarding leverage usage.

In an interview with ValueWalk where managed futures analysis concepts were overlaid against their DSA modeling, Markov and Li estimated QuantEdge’s leverage at near 3 to 1 leverage. “Leverage is the primary risk factor in the strategy,” Markov said, noting that a fund that is up 44% one year can easily be down by similarly strong double digit numbers the next year.

Looking at their internal models, Li estimates the fund strategy to have discretionary components and may not fit a pure definition of a systematic managed futures strategy, but he acknowledges that it could be systematic with a dynamic strategy. Systematic strategies are defined as being entirely rules based and follow a consistent mathematical formula. Managed futures strategies, as the name implies, have traditionally been defined by the derivatives contracts traded.

“The global macro and CTAs are the two hedge fund strategies that are mentioned most often in the same breath,” he said, also pointing to categorization in the HFR and Eurekahedge performance databases. “The main difference, in my view, is that CTAs are pure quantitative strategies, which are supposed to make money regardless of market fundamentals. “Global macros, on the other hand, care much more about market fundamentals and use them to make trading decisions.”

Assuming that the Wall Street Journal report is accurate — and it differed from Markov’s analysis in certain respects — the program could benefit in today’s market environment of relative rising short rates. While QuantEdge’s exact positioning and strategy is unknown, if they are truly short the short end of the spread and long the long end one the Treasury curve,  today’s market action and any related market volatility the strategy might encounter would be considered positives in an uncertain environment.