Stockholm (HedgeNordic) – Many trend-following CTAs have profited in the first quarter of 2020, and most of Systematica’s various trend-following strategies have outperformed the industry averages. One variable differentiating returns of CTA managers has been the speed of their models. In both late 2018 and early 2020, shorter term models proved to be more defensive. And in 2020, shorter term traders in general have outperformed other CTAs: Societe Generale’s SG Short-Term Traders Index advanced 4.3% in 2020 to April while the SG Trend Index was up 2.47% and the SG CTA Index was slightly negative at 0.3%.
Timing is of the Essence
Systematica sits at the shorter-term end of the medium-term trend following category, whereas some other CTAs have slowed down their models between 2009 and 2017, according to statistical analysis of the SG CTA Index revealed in Systematica’s Research Soundbite Series paper, “Is the world a slower place?”. The SG CTA Index is made up of ten of the largest CTA funds.
A shift to longer term models is possibly a consequence of asset growth since shorter term strategies are less scalable. It could also have been an opportunistic response to market behaviour: slower trend following models worked better during much of the post-GFC period, riding multi-year trends in bonds and equities.
Pure Trend or Multi-Strategy Quant?
Some CTAs have also added non-trend strategies, such as volatility arbitrage; fixed income arbitrage; relative value; and equity market neutral or statistical arbitrage, to their trend following funds, which has in effect created multi-strategy quant programs.
Systematica offers a granular strategy menu: these non-trend strategies can be accessed separately or via multi-strategy vehicles, and there are also three mainly or wholly trend-following strategies available on a standalone basis. Two of these trend following strategies, BlueTrend and Systematica Alternative Markets, have a 10-15% sleeve in non-trend strategies, both macro and relative value, and one is a pure trend following strategy, Systematica Trend Following.
“We restrict the risk allocated to non-trend in BlueTrend and SAM because those funds are not multi-strategy funds – they are trend followers (TFs). TFs have a very unique and desirable correlation profile and institutional investors tend to have the technical insight into that. Non-trend strategies may have higher expected Sharpe Ratio but not the same defensiveness of TFs. For investors who want a multi-strategy quant fund, we offer customised mandates and also a dedicated multi-strategy fund”, explains Systematica CEO and founder, Leda Brag (pictured).
The latest innovative approach to trend following, BlendTrend, is being deployed as part of some of Systematica’s programmes.
Plain Vanilla Trend Following
Systematica’s best performing trend strategies in the first quarter of 2020 were BlueTrend (up 9.78% in USD) and the firm’s plain vanilla, flat fee, 100% trend following program, Systematica Trend Following (STF) (up 7.38% in USD), which is also one building block for its alternative risk premia (ARP) strategy, both of which come under the umbrella of “scalable alternatives” and the former is available in UCITS format. STF trades only around 90 major listed liquid markets (with no OTC markets) and uses only pure trend following signals, but it still uses the firm’s proprietary models, portfolio and risk construction methods and algorithmic trade execution.
Yet more traditional trend following approaches have, over the past decade, sometimes experienced challenging performance for multi-year periods. Notwithstanding the powerful diversification benefit at the portfolio level during some market crises, some investors cannot tolerate long periods of lacklustre numbers.
Two avenues of innovation designed to increase Sharpe ratios have been: diversifying into less widely followed OTC markets, and refining models to use new forms of data and signals.
OTC Markets
Systematica was one of the first CTAs to start trading OTC markets, which founder and CEO, Leda Braga, and CIO, David Kitson, had extensive experience of during their earlier careers: Braga was pricing exotic derivatives at JP Morgan and Cygnifi Derivatives Services and Kitson was trading them on the JP Morgan prop desk. Systematica’s oldest strategy, BlueTrend, which started in 2004, traded forwards; emerging market FX; equity sector swaps; interest rate swaps and commodity swaps on an OTC basis before Systematica Alternative Markets (SAM) launched in 2015, further expanding OTC coverage and offering exposure purely to these markets. As of 2020 Systematica is trading over 270 OTC markets, and using multiple counterparties to access them, including via “high touch” voice execution carried out by a global team of human traders.
“Better alpha opportunities and larger internal diversification lead to superior returns on OTC relative to traditional markets trend-following post GFC.”
The OTC markets that SAM trades include credit indices; equity sectors; interest rate swaps; emerging market FX and alternative commodities such as coal, iron ore and electricity. In some cases, the OTC markets offer access to markets for which futures do not exist. In other cases, they are larger and more liquid than the futures markets on the same underlying. This investment universe has generated better returns from trend following than have traditional, futures markets, during most of the post-Great Financial Crisis period. This is because, “OTC markets are less influenced by risk-on risk-off dynamics than traditional CTA markets. Better alpha opportunities and larger internal diversification lead to superior returns on OTC relative to traditional markets trend-following post GFC”, argues SAM product manager, Matthias Hagmann, who worked on a similar OTC trading strategy in his previous tenure. Systematica has also hired a number of former sell side and discretionary traders to further grow OTC coverage. The SAM program has received a number of performance awards.
BlueTrend has a material allocation to alternative/OTC markets, and this sleeve is expected to grow over time although clients will always value the liquidity and long track record of futures markets.
BlendTrend
One other engine of innovation – model and data refinements – can be sub-divided into four themes. To adapt models to the potential cyclicality and seasonality of trend patterns, it is possible to introduce variable time lag delays to frame the lookback period used to define trends. Another approach is to use price moves in one asset class to generate signals for other asset classes, which can be dubbed “cross-asset signals”; machine learning techniques are used to divine these indicators. Two other perspectives change how the investment universe is grouped.
Whereas traditional trend following identifies trends in individual markets in isolation, trends can also be defined at the level of asset classes (equities, bonds, currencies, commodities) – and implemented by trading baskets of markets. Or trends can be viewed through the prism of Macro factors, which can apply across multiple asset classes, but which could still be implemented via trading individual markets. These factors are persistent and broadly relate to wider economic themes such as risk on/risk off, liquidity and inflation regimes.
The combination of these four formulations is BlendTrend.
Systematica has spent years developing and backtesting these models and arrived at the conclusion that they have suffered less decay of returns than traditional trend following, while still being correlated to traditional trend following and offering similar defensive characteristics. Therefore, BlueTrend started allocating to them in 2019 and by 2020 BlueTrend had 25% exposure to BlendTrend, which may also grow over time.
“The challenge with trend-following is consistency in the non-crisis periods and modelling innovation must be the answer to that.”
Some investors have also expressed an interest in accessing a pure play BlendTrend strategy.
To put it in Leda Braga’s words: “The challenge with trend-following is consistency in the non-crisis periods and modelling innovation must be the answer to that.”
This article featured in HedgeNordic’s report Systematic Strategies: When Numbers are the Key!
