We are frequently asked how investors should analyze the performance of managed futures strategies. This is quite challenging due to the diversity of the strategies employed, and the non-constant exposure, both long and short, across one or more asset classes (i.e., stocks, bonds, commodities and currencies). Because of the lack of consistent exposure, a standard benchmark like the S&P 500 Index is sub-optimal, to say the least, but there are ways to suss out a manager’s value add.
While admittedly failing most of the criteria needed to be viewed as a valid benchmark, peer groups can serve as an attribution tool in a sense. Meaning that the purpose of conducting attribution analysis is to determine the efficacy of the decisions made against the decisions that could have been made. As such, a peer group can also serve as a proxy. Even still, we’d suggest caution when judging a managed futures fund against the peer group. If Manager A outperforms its peer group over a 1-year period, as an example, does that mean that Manager A is superior? Putting aside the fact that such a short period wouldn’t be statistically significant, we can’t draw that kind of conclusion. If all of the managers are trend followers, but they measure trends differently and over different time frames, mere outperformance over a year says nothing about the efficacy of Manager A’s models, other than that they worked well over the specified time period. Over a full market cycle, relative performance should provide some insight into the superiority of the particular models employed, but again, we’d suggest drawing such conclusions with care.
So where does that leave us? Standard benchmarks are of no use and peer groups are lacking as well. Therefore, investors need to look at benchmark independent measures of risk-adjusted return, such as the Sharpe Ratio, Sortino Ratio and Omega Ratio. Given the ubiquity of the Sharpe Ratio, we won’t spend time on that metric, except to say that its assumption of a normal return distribution and its equal treatment of upside and downside volatility makes it less than ideal. Sortino Ratio is similar to the Sharpe Ratio, but uses an investor’s Minimum Acceptable Return in the numerator and Downside Deviation in the denominator. Doing so makes the ratio more relevant to each investor’s specific goals and directly addresses the fact that we all feel the pain of a loss more than the joy of a gain; upside and downside volatility are not the same.
Turning to the Omega Ratio, it’s likely that for most readers this is new term. And you might be asking why do we need yet another risk-adjusted performance measure? The benefits of the Omega Ratio are many. Like the Sortino Ratio, it doesn’t penalize outcomes greater than expected, and it addresses a target level of return. In addition, Omega is calculated using the actual return distribution of an investment, so it doesn’t rely on an assumption that returns are normally distributed. Further, Omega is intuitive in that the higher the ratio for a given return threshold, the higher the probability of generating returns that meet or exceed the goal. The fact that it explicitly takes into account probabilities makes Omega a useful addition to our palate of risk-adjusted return metrics.
Lastly, in addition to comparing the risk-adjusted ratios of different managed futures funds, we’d add that you need to stop and think about what you are trying to achieve with an allocation to managed futures in order to judge the effectiveness of the investment generally, and the manager specifically. The typical rationale for investing in these strategies is the desire for a true diversifier, that is, one with a low correlation to equities and fixed income, that can also generate a meaningful real return in a variety of markets. Investors evaluating managed futures funds should consider all of these factors—risk-adjusted metrics, rolling correlations to other assets, and performance in down markets—when evaluating the effectiveness of these types of investments.
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