Managed Futures – 2022 Review
Buckle up because the folks at Mt. Lucas have brought it with the below analysis:
2022 was a banner year in the Managed Futures space. Stocks and bonds both had a tough time, something that’s fairly rare. The S&P 500 Total Return Index returned -18.1%, the Nasdaq-100 Total Return Index fell -32.5%. The Nasdaq saw its high for the year on the opening day and the low a couple of days after Christmas. The Bloomberg US Agg Total Return Index returned -13.0%. The chart below illustrates how infrequent negative returns are in both asset classes.
If there was a year when a strong Managed Futures return would be most helpful, 2022 was it.
Below we will examine how investors use the asset class and review the key drivers of returns last year. We will then analyze the various quantitative approaches to trend following, how they explain dispersion among managers, and how they have performed historically and in 2022, when needed most.
Overview – Managed Futures
Many investors look at Managed Futures through a lens of absolute returns over economic cycles, uncorrelated to stock and bond markets. This lens looks at the broader range of markets available in Managed Futures – currencies and commodities typically – and both the long side and short side of return distributions available such that one isn’t reliant on prices always going up to generate positive returns. Either up or down is fine, as long as prices trend. Choppy sideways is bad.
Other investors look for Managed Futures as ‘Crisis Risk Offset’ strategies that they expect to generate returns during equity market declines and recessions, somewhat akin to put options or highly rated government bonds. This lens sees Managed Futures as capitalizing on flows that recessions and panics tend to coincide with – equity markets down, commodity markets down, flight to quality dynamics in currencies and fixed income.
In 2022 Managed Futures certainly delivered on both these counts, providing uncorrelated returns in the worst 60/40 market in decades.
In Part 1, we use the MLM Index EV methodology to examine how Managed Futures generated returns in 2022, looking in detail at the underlying market moves by asset class, highlighting some individual positions that contributed, and showing how some of the different approaches to Managed Futures impact returns. The MLM Index EV does a fine job at explaining and capturing the beta we believe exists in the space and using some different derivations in the parameters can offer some insight, particularly in big, interesting years.
In Part 2, we deconstruct Managed Futures returns into their contributing factors. Performance dispersion for any given Managed Futures strategy is generally driven by some combination of the following approaches by each manager:
Volatility – the level of overall strategy volatility that is expected or targeted
Trading speed – short, medium, long or blend lookback
Trend approach – simple moving average, slope, crossover, breakout, etc.
Market universe – more markets, less markets, alternative markets, sector allocation
Position/Risk management – how positions are sized, rebalanced, and volatility adjusted
Of course there is more going on, but in the same way equity indices can be constructed to target different styles or factors like growth/value, low volatility or by sectors, Managed Futures returns can be somewhat deconstructed along the lines above. It can be useful to take a look in detail at how each of the changes impacts the nuances of Managed Futures results.
Part 1: The Year in Review – The Macro and the Beta
On a macro level the year was dominated by a few large themes, somewhat related. As with all things, it is generally unwise to treat anything with many shifting possible but unknowable drivers as monocausal or bicausal. With that said, 2022 in Managed Futures was primarily driven by the war in Ukraine, particularly in the first half, and rising interest rates coursing through asset markets.
How did Managed Futures benefit from these macro themes? To explain, we will first show the performance of the MLM Index EV over the long term, then zoom into 2022. The quick primer on this index: it represents pure trend following using a simple moving average, long term lookback, taking long and short positions in commodity, fixed income and currency markets with an expected volatility of around 15% annualized. Note – this index does not take equity index futures positions.
The total return index better describes an investor experience as it includes the return on cash held by the strategy – which last year for the first time in a decade was a quite meaningful addition. Once we drop into attribution for individual sectors and markets we use trading returns, which exclude the return on cash. Those charts will be shown in orange to delineate.
Source: Mount Lucas
One can broadly see the two different surges at the index level, the first through April, the second in the third quarter. Breaking these down by asset class and then including a couple of example positions can be useful to get an understanding of how the index participated. The first surge centered on the commodity sector, which we look at below. While oil markets dominate financial news on commodities, Managed Futures strategies trade a wider set of markets across the broader energy complex, agricultural markets and metals.
The charts below show crude oil and wheat prices as a typical Managed Futures strategy would see it – a synthetic continuously rolled futures contract time series. From 2021 to the end of 2022, the crude oil uptrend was already in place entering the year, which then accelerated as the war in Ukraine rattled the oil markets. Again, with the caveat that things are not monocausal, broadly speaking things calmed down in the second half of the year as releases from the US Strategic Petroleum Reserve aided supply and demand was reduced due to pandemic restriction in China.
Looking at the wheat market, we see a largely steady but slightly up trending market entering 2022 which then spikes aggressively; up 50% in the first quarter. The MLM Index EV trend models had long signals through this period, contributing to commodity sector returns in the first part of the year.
Interestingly in a year characterized by inflation fears, gold did not react in a meaningful way. We wrote in a recent blog about how trend following strategies differ and improve on macro approaches that attempt to balance portfolios across macroeconomic regimes or move asset allocation to favor different regimes. Those approaches rely on asset prices doing what they are ‘supposed’ to do, which they don’t always do. Gold is a good example – faced with rapidly expanding money supply and much higher inflation than expected, as well as global political uncertainty, one would have been forgiven for having assumed gold over the past couple of years would have moved strongly up. An almost perfect storm for it – high inflation, high geo-political uncertainty, massive money printing and balance sheet expansion. Did it perform very strongly, as those macroeconomic models would have likely assumed? It did not. Managed Futures lets these things shake out – the ‘following’ part of trend following. If it goes up, great…If it doesn’t, not the end of the world.
The last commodity example we are going to highlight as notable is Natural Gas. The contract here is the US benchmark contract that had large and volatile moves over the course of the year. Similar large price moves in the first half of the year driven by the Ukraine invasion, which then subsided somewhat as the year ended.
The Managed Futures returns in the second half of the year were more directly driven by monetary policy and divergent growth. Global central banks raised interest rates rapidly as inflation rose. From the starting point of very low global yields, negative in some places, bond prices fell hard. Relative interest rate differentials and growth outlooks are often meaningful drivers of currency markets. Here we treat fixed income and currency markets together. The main story in these sectors in 2022 was the rise in the USD against the major developed currencies, and rising global yields.
War impacted European economies more than the US. The Euro fell, growth weakened. Inflation caused the ECB to raise rates for the first time in a decade.
Japan continued with negative interest rates and until the end of the year maintained the yield curve control policy keeping 10 year yields under 0.25%. In a world where the US was hiking rates 75bps every six weeks, JPY plunged.
In the UK, chaotic policies poured fuel onto the fire of an already weak GBP, and a bond market revolt saw the end of a Prime Minister.
The MLM Index EV models participated in all of these moves. The charts below show the past 36 months of net exposure by sector in each of the asset classes.
Staying at a high level – this is how Managed Futures can work to diversify stock and bond portfolios in crises. They are able to take positions in exactly the sources of stress for equity markets – in this case, direct exposure to commodity markets, global yields and currencies, the movements in which cause volatility in equity markets. Crucially, over time the drivers alter, so the required diversifying position alters. In 2008 the right Managed Futures positions were short commodity markets, long bonds and long the USD. This time around, two of those sectors have flipped signs. The right exposures to diversify stocks were on the short side of bond markets, capitalizing on rising yields and the long side of commodity markets.
Part 2: Managed Futures – Trend Following Deconstruction
To capture the investor risk premium in the equity markets the dominant trading strategy is buy and hold. To capture the investor risk premium in the futures markets the dominant trading strategy is trend following. In equities, buy and hold can be implemented in a variety of ways: market cap vs equal weight, value, growth, quality, momentum, concentrated, etc. Trend following can be deconstructed using a different set of factors. These include volatility level, trading speed, trend approach, universe, and position/sector sizing. Understanding each of these factors is a good start to unpacking the different outcomes. Below we have run some illustrative models isolating each of these factors in turn.
This one is the simplest to get to grips with. Given the way in which futures contracts inherently allow leverage (if they didn’t, their ability to be useful tools for physical market hedgers would disappear) one can take exposures over 100% of NAV. This is also necessary to approximately equalize risk between markets with very different levels of volatility. As a rule of thumb, bond markets are less volatile than developed currency markets, which are in turn less volatile than commodity markets. In order for these different sectors to equally contribute to the strategy, you need more exposure in bonds than commodities. As the Managed Futures space has matured over the past 40 years or so, and its role as a portfolio diversifier has increased, Managed Futures strategies have generally landed on targeting an overall volatility similar or just below the stock market, about 10-15% annualized. The first driver of differences – what approximate level of expected, or targeted, volatility is utilized by each manager. The charts below show the performance and rolling realized volatility of the MLM Index EV – run at expected volatilities of 5%, 10%, 15%.
In 2022, a 15% volatility version of the MLM Index EV returned 36.7%, a 10% version retuned 24.5% and a 5% version 12.75%. The point, however, is that each version employed an otherwise identical approach. When comparing the results of different Managed Futures strategies, adjusting for differences in intended volatility for each manager is the necessary first step.
Within Managed Futures strategies, managers need to decide how a trend is determined and what the appropriate look back period is to assess the context of the current price. In practice most managers use a blend, applying multiple lookback periods in order to smooth out and diversify signals over time. Typically, the industry would categorize ‘fast’ models as those with look back periods in the range of a few weeks to a couple of months, ‘medium’ models look back several months, and ‘slow’ models look back 9 months to a year.
The chart below shows the results of a model portfolio using the same methodology as the MLM Index EV above (plus equity index futures), using different lengths of time to calculate trend signals on a simple moving average. Over the longer term, performance has generally been better at the slower end.
Although over any shorter period this can go either way, 2022 was true to form.
There are many ways to run trend following models, we look at a few of the classic ways here – again only changing the model type and keeping everything else the same. We use moving averages, a spline approach for slope of a market, moving average crossovers, breakout models and exponential moving averages. Many more exist – and if you compare with all the possible parameter sets (of which we have only scratched the surface) you get many possible permutations.
Worth restating, these models are for illustrative purposes, we have made what we believe to be reasonable ‘non-optimized’ parameter assumptions. Overall, they all somewhat rhyme, and with good reason. To revisit the Japanese Yen chart above, when a big move like that is taking place, all approaches will put you into a short position for the bulk of the move. Differences in trend approach will determine how quickly a strategy gets into or out of that position, and how that position is sized.
The 2022 experience – a fair bit of variation, lots of correlation. The final race leader chart shows how the different approaches overtake each other as time passes.
Correlations of approach, all else equal.
Another determinant of Managed Futures performance lies in the universe of markets included in the model. Our stance is that we want to be broad enough for appropriate diversification, but at some point having many markets naturally reduces the amount of risk that can be allocated to the major markets for the same overall risk level. Given the extra diversification in adding many extra markets, one can increase overall leverage to some extent – but not enormously. We believe that there is value particularly in a portfolio context in keeping exposure close to the major markets – we wrote more here. Over time, adding more markets as we have defined the universes here (keeping sector exposures the same, only adding new markets when we think it would have been reasonable to do) increased possible returns some, but in 2022 it was a wash.
Typical Markets – 27 major markets across commodity (11), currency (6), fixed income (5), equity (5)
More Markets – 72 markets across commodity (25), currency (14), fixed income (16), equity (17)
Volatility Adjusting – Inverse Volatility Sizing
Many Managed Futures strategies will volatility adjust positions in response to current levels of volatility, within reasonably acceptable ranges. Inverse volatility sizing works as the name implies. The higher the market volatility, the smaller the position; the lower the market volatility the larger the position. There are many ways to measure volatility – different look back periods, implied volatility, recent ranges, etc. The difference between volatility adjusting and not – letting positions continue at original target size – is often small but can be material in times of stress (think 2008 when stock markets gapped down post the Lehman bankruptcy, existing short positions would be reduced under many volatility targeting approaches). In other times, the last volatile crescendo of a move can be a great time to reduce positions as it may spur corrective action from governments – think the last moves in UK Gilts that played a part in the downfall of Liz Truss. We explain our view on how this impacts Managed Futures portfolio skew and how that interacts with other asset portfolios here.
The chart below shows performance of the slow trend model used above, which sizes positions based on fixed notional exposures, versus the same model using inverse volatility position sizing.
In periods of stress volatility adjusting makes a difference. In 2022 as the war started and markets spiked, it becomes a question of whether one wants the extra skew when stock markets are getting particularly hit, at the expense of some larger drawback later. In a world of regular rebalancing, the skew is valuable. As a standalone investment, the smoother ride may be more desirable. Inverse volatility sizing gives up the right tail of the performance distribution (positive skew) in exchange for a better Sharpe Ratio.
In looking at an individual position using the illustrative models you can see this in action. Here we look at the crude oil move, using one model speed position with and without volatility targeting. As the price starts to spike in March 2022, volatility adjusting reduces positions aggressively as volatility also spikes, limiting gains in the spike part of the move and reducing losses later. Rebalancing through these moves matters a lot.
It is easy to get caught up in weeds of which volatility, or speed, or approach, or position sizing method is best, but in our view these are secondary considerations. The single most important decision regarding the addition of Managed Futures to the portfolio is exactly that – just doing it, sticking with it, and rebalancing aggressively. The second most important thing, doing it cheaply and efficiently. After that, happy to debate.