Managed Futures and CTAs: A Smorgasbord

BY DR. AJAY DRAVID, EQUINOX FUNDS CIO


ALL CTA PROGRAMS ARE NOT CREATED EQUAL

Historically, over the last thirty-five or so years, the managed futures asset class has become synonymous with systematic trend-following CTA programs that actively trade futures or forward contracts. It is important to understand that not all futures-trading strategies fall under the managed futures umbrella as conventionally defined, and that even some well-known research and ratings agencies have on occasion ended up misclassifying some funds and strategies as managed futures. Conversely, some CTA programs that implement strategies other than systematic trend-following may still be legitimately classified as managed futures.

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Conventionally, many market participants tend to think of a managed futures strategy as a CTA program with the following characteristics:

    • The program trades in multiple global futures markets (generally ranging from around 25-50 at the low end to more than 200), diversified across six major sectors–stock indexes, fixed-income (including short-term interest rates and bonds), currencies, energy, metals, and agricultural commodities.
    • Trading is primarily systematic, although some discretionary traders do exist. Systematic trading is based on quantitative models and algorithms and generally involves very little if any manual intervention or decision-making, other than in extreme situations.
    • Trading is active in the sense that the models are generally run at least daily, if not more frequently, and positions are initiated, modified or closed out based on the outputs from the models.
    • The strategies employed are generally based on medium-term to long-term trend-following, but may include relative value trading, counter-trend or contrarian trading, mean reversion, pattern recognition, short-term trading, etc.
    • The program utilizes risk management techniques such as stop-loss orders, dynamic position sizing, volatility targeting, etc.1

A quantitative technique that can serve as a rough diagnostic test in evaluating futures trading programs is a correlation matrix that examines how the returns on a strategy correlate with other futures trading strategies and with recognized managed futures benchmarks such as the Barclay BTOP50 Index®. The correlation matrix for a selected sample of CTA programs and asset class indexes is displayed as an illustration below2

Our sample consists of sixteen CTA programs. The first eight among these are purely or primarily trend-following. The next two programs contain some element(s) or variant(s) of trend-following. For convenience, we refer to all ten of these programs as “trend” programs hereafter. Our sample of six “non-trend” CTA programs represent other trading styles such as spread or relative value trading, short-term trading, short-term pattern recognition, and discretionary and systematic global macro. Brief descriptions of all sixteen CTA programs are presented in the notes to the right of the correlation matrix. We also include in the correlation matrix five asset class indexes that are proxies for managed futures, US bonds, long-only commodities, US stocks, and world stocks.

Correlation Matrix

What determines correlation?

Why do different CTA programs have different correlations with stocks or other asset classes?

We can identify some potential explanatory factors.

All CTA programs are not created equal. First and foremost, they can be broadly classified as systematic vs. discretionary, and trend vs. non-trend. The vast majority of CTA programs are based on systematic trend-following. However, the managed futures space includes several other trading styles: discretionary, global macro, relative value, mean reversion, pattern recognition, counter-trend, sector-specific, etc.3 A trend following CTA program is likely to have correlations to other asset classes that may be quite different from those of a relative value trading program.

Across CTA programs, and particularly within trend-following programs, trading or look back time horizons may range from short-term (2 days – 2 weeks) to medium-term (2 weeks – 2 months) to long-term (2 months – 2 years). Again, the correlation of a short-term trading program to stocks, for example, may be very different from that of a longer-term program.

While the majority of CTA programs tend to be diversified across market sectors, and trade in multiple futures markets (quite often between 25 and 200), some sector-focused programs do exist. For example, there are CTA programs that focus on only physical commodities, others that may have a risk “overweight” to energy, and some (albeit fairly small) programs that may be even more narrowly focused on, for example, mainly meats and grains. The correlations of an energy-focused program with other asset classes are likely to be quite different from those of a broadly diversified CTA trading program.


1For more details, please see our Insight, “Managed Futures: Risk Management in CTA Programs,” (2017).
2Pages 2-3 display CTA programs currently accessible through Equinox Funds.
3See our Insight, “Principal Component Analysis: A Tool for Analyzing and Describing CTA Programs” (2016).

Diversification does not ensure profit or prevent losses. an investment in managed futures is speculative and involves a high degree of risk. You can lose money in a managed futures program. there is no guarantee that an investment in managed futures will achieve its objectives, goals, generate positive returns, or avoid losses.