What’s more, the “anti-correlation” between stocks and bonds, Seager said, is not likely to hold up in the current environment, which means that institutional investors need to look at other approaches not only for diversification, but also for return enhancement and downside protection. Macro strategies, when executed properly, can provide genuine diversification of stocks and bonds, he said.
Technological advances in machine learning and quantitative techniques mean that systematic global macro, or SGM, strategies may provide the protection that institutional investors have been seeking. As the availability of data across every industry and sector of the economy grows, so too does the potential for institutional investors to harness the power of that data to hedge the downside risk of equity.
Leveraging its deep background in trend-following, CFM built its SGM strategies with adapted trend-following characteristics to enhance a portfolio’s diversification and provide that downside hedge, which Seager said aligns with what pension fund plan sponsors and other institutional investors are seeking.
“Invariably, pension funds or institutional investors are sitting on big piles of equities and are trying to diversify away from them, but it’s very difficult to do with traditional instruments,” he said. “We are providing the diversifier of core macro strategies and on top of that, we have a hedge component. And I think that really suits institutional investors.”
Refining an existing approach with new tools
Exploiting effects, or factors, in capital markets to capture alpha is nothing new for CFM, which has been trading in futures markets since 1991 and systematizing macro ideas for the past 15 years, since it began researching the conversion of discretionary ideas into trading systems and exploiting their potential to deliver positive returns. In recent years, CFM has refined its approach, incorporating new machine-learning tools and techniques to help analyze vast amounts of data to build new strategies. It launched its SGM strategy in November 2020.
According to Seager, now is the right time to employ SGM strategies mainly because of advancements in technology and growth in data. CFM’s directional, fundamentals-driven SGM strategy uses traditional macro data inputs, such as gross domestic product and inflation, but also constructs growth and inflation proxies from other data sources. The firm then isolates clusters of performance drivers to build long-term models that trade liquid investments across global futures markets. Finally, it applies a defensive layer to provide equity protection.
“Only algorithms are able to treat this vast amount of data, make sense of it and build strategies with it,” Seager said. “Algorithms are ubiquitous in everyday life. For example, they are used in piloting an aircraft, medical procedures, apps, and more. In investment, algorithms are used to absorb, treat and analyze vast amounts of data to make investment decisions. It is our belief that this trend will continue and that algorithms will have an increasing advantage over discretionary investors over time.”
He added that because of the growth and evolution of algorithms beyond finance, investors have become more comfortable than ever with the type of financial engineering that SGM employs.
“This macro approach is naturally easier to follow and to explain because you move away from the black box,” he said. “There is an intuition behind it, and you can explain that. So I think in that sense, it’s easier to get across because there’s always a narrative for pension plans and institutional investors to follow.”
Diversify and hedge
The defensive layer is of particular interest to institutional investors who have struggled to use traditional investments and assets as a hedge against their equity holdings. One common approach they have used historically is option strategies. But while options may offer protection, they can be expensive and generate a significant negative drag on the portfolio.
“Diversification is one of our core beliefs. It’s inherent to our philosophy,” Seager said. “And the more independent bets you have, the better outcomes you can achieve. We think having a portfolio with many different factors across many different asset classes is going to generate better outcomes.”
That’s particularly true given the stage of the current market cycle, and as the U.S. and other global economies potentially enter a period of long-term inflation.
“Equities have been in a long-term rally since the global financial crisis,” Seager said. “The long rise in performance looks good in isolation, but [when] expanding the big picture and looking over long histories, one sees that these rallies are also accompanied by significant crashes [resulting in] modest risk-adjusted returns.”