Giuseppe H. Robalino

 

The “market,” here, is meant by a series of indices attempting to track managed futures. This cannot be simple to do. There is a variety of investing styles, strategies, and positions CTAs—commodities trading advisors—can chose to follow. Some focus on energy, some on agriculture, some on metals; others trade currency or interest rates. Yet, there are also those who combine commodities and even bet on regular asset classes into over-arching strategies known as “diversified,” “discretionary,” “systematic,” or “trend following.” The list goes on and on.

 

What does a strategy like diversified even look like? What about discretionary—in which a manager can switch strategies/styles as market conditions change? So how can this all be tracked?

 

An in-depth article in  Bloomberg explored just how well these investment vehicles are understood. The consensus seems to be that very few advisors actually do understand. They are unsurprisingly complex—as futures trading certainly can be. Some advisors also struggle to make sense of how these indices are even constructed, given contracts’ differing expiration dates and the varied structure and allocation of the funds themselves.

 

Perhaps one way to look at them would be to assume that, at any point in time, there is a permanent float of unexpired contracts in each fund. After all, a single fund can invest across multiple timeframes. But then, what index should advisors use?

 

As we will see in the case study below, a managed futures fund may not always correlate well with the manager’s given index. In other cases, as shown in the Bloomberg article, not all indices show the full story, either. The index touted by the CME, the Barclay CTA Index, operates only on volunteered information and does not deduct fees.

 

So, given this confusion, why invest in them? Depending on their structure, they can be very useful in mitigating a portfolio’s tax expense; some funds invest in companies overseas that execute trades tax-free. Managed futures are also non-correlated to the general market, adding to a portfolio’s diversification.

 

However, since they are non-correlated, few can predict in what direction they will take a portfolio; they can outperform in a bear market, but underperform in bull market. Yet, if the futures strategy is not allocated in booming sectors, that part of a portfolio can remain flat.

 

According to the CME Group, managed futures can help reduce a portfolio’s variance, and drawdowns have been historically lower than other hedge fund strategies, particularly those tracked in the HFRI and the S&P. However, it also warns of the risk of managed futures strategies falling prey to curve-fitting and over-optimization. This is a particular issue with market timers. And just who did Ben Graham warn investors about?

 

An advisor who considers a managed futures manager needs to pay careful attention to those two things. If a manager unwittingly curve-fits, he is making decisions on the future based on models that focus on replicating past performance. And, if there were to be any ten commandments on investing, one of them would surely be the now commonplace disclaimer, “past performance is not indicative of future results.”

 

A Case Study: ASFYX

 

A predominant strategy some mangers have chosen is to trend-follow. Now, it is important to note that passive managers rival active managers. They make the case to buy into indexed managed futures funds, arguing that it is difficult for active managers to generate alpha—enough to justify fees, that is. And, while trend-followers can be very profitable, they suffer when they follow trends into a mean-reversion.

 

In somewhat of a defense for active managers, however, some of their models—particularly trend-following ones, can get quite sophisticated. Let’s look at a relatively simple, yet very interesting case study: ASFYX.

 

This is a relatively new fund and is in mutual fund format. It was established in 2011 by an MIT professor specializing in algorithmic investing and behavioral finance. He created the Adaptive Market Hypothesis,which his fund unsurprisingly follows. According to the hypothesis, markets are neither fully efficient nor rational. It is mostly trend following, but also targets volatility above that of the S&P.

 

ASFYX is allocated across commodities, equities, interest rates, currencies, and fixed income. It has been short the last two. With a 3-year alpha of 3.35 and a YTD return of 12.75, it seems as if it has certainly been delivering performance.

 

However, while these numbers are good—it is only correlated to the Credit Suisse Managed Futures Index by 40.10%, according to Morningstar. And, while in their letter to investors they pledged to deliver the best Sharpe possible—despite their target 15% volatility—it has substantially plummeted from near 1 in 2011 to -0.12 in 2013. ASFYX rallied in its first year, plummeted in 2012, and barely eked out positive returns across its 3-year performance.

 

For 2013, it likely survived due to its equity exposure throughout the year, along with its fixed income shorting at the end of the year. Sources reveal its currency strategy was helpful, which makes sense given Abenomics’ easy money in Japan.

 

Its bias towards equities may need to be corrected for 2014. This is especially crucial since historically, the S&P has not rallied more than 6% after a prior year rally of over 20% or so. 2012 saw a decline in interest rates, but it seems as if ASFYX kept a large, though variable, exposure to interest rates from 2011 to 2013. In 2013, it seemed to be highly levered at 336% long interest rates! Note that Bloomberg reports that, in this industry, only 10% down payment on margin is required, unlike the 25% minimum for investors at the NYSE.

 

It is still unclear, given its 3-year life how it will continue to perform. Only time will prove the long-term efficacy of its trend-following models and many have actually failed overtime, even after working for a decade. How sustainable its alpha may be—given its young age—remains to be seen. An advisor would be prudent in lightening exposure, but keeping a watchful eye over its performance over the next few years, balancing that against its current S&P 1500 beta of 0.48, since we face a trade-off of good returns versus non-correlation.

 

So what to do?

 

A final point for advisors to keep in mind is that some experts point out that managed futures are not bought for performance—but as a manager of variance and risk. For diversification, and not returns. Is there a future for managed futures? There certainly can be, but with increased correlation across asset classes and certain markets, it is difficult to find uncorrelated safe havens.

 

A working paper by the Imperial College of London has shown that it is not even capacity constraints on CTAs that make producing uncorrelated alpha difficult—but possibly the nature of the correlation of markets themselves, post-crisis. Additionally, an advisor needs to look out for egregious fees and commissions, find his own best-fit index, and avoid market timers. This is a highly marketed, arguably lightly regulated industry.