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Hedge Fund Strategies Tweaking Algorithms Were Big Winners in 2017

By ValueWalk
Hedge Funds


For certain hedge funds, 2017 might be considered the year of the strategy adjustment – and the attainment of alpha over the performance of an index. This is particularly true among noncorrelated hedge funds, those strategies that are not entirely dependent on the performance of the stock market.

Cantab’s multi-strategy system significantly outperformed their benchmark

The top-performing hedge funds on the HSBC Hedge Weekly report revealed outperformance divergences. Some funds significantly exceeded their benchmarks – while other funds road both a strong beta market environment in delivering overall 6.5% returns basis Hedge Fund Research data reported by Bloomberg.

With the US stock market up near 20% in 2017, a 6.5% return might seem rather mundane. But with some hedge funds, the goal is not absolute returns, but rather a potential protective return stream during extended stock market downtrends.

Normally this strategy category can be challenged by market environments featuring dulcet volatility – as has been the case during the quantitative stimulus era – but some of the funds outperformed in 2017, significantly separating themselves from their beta benchmark.

London-based Cantab Capital Partners Quantitative Fund Aristarchus, with $1.9 billion under management, was up 30.97% in 2017, for instance. The Managed Futures strategy meaningfully outpaced the muted 0.25% HSBC Managed Futures category performance and the -0.14 SG Trend Indicator, one of several CTA benchmarks that mostly delivered limp returns with the stock market heading higher.

But it is not the beta of trend following that entirely mattered to Cantab.

Cantab’s multi-strat approach generates outsized returns, while DUNN adjusts trend models

The Cantab Aristarchus Program uses a multi-factor approach to Managed Futures quantitative investments. This industry is traditionally rooted in one primary strategy, momentum (trend following). But some have been making strategy adjustments to this core approach that delivered positive performance in 2008 due to the extension of trend momentum.

Key performance driver concepts include integrating different revenue streams by combining noncorrelated volatilities – which is the case with Cantab. The strategy uses momentum but also integrates a value and short-term model into their strategy. While the more than 100 markets traded is consistent with consensus managed futures diversification, their trading ranges skew to the mid-term to short-term time horizon, according to Altegris data.

Other strategies successfully stick to the core trend following model but have a history of constantly researching strategy tweaks, as is the case with Stuart, FL-based DUNN Capital.

The nimble DUNN WMA Offshore fund, with $74 million under management, posted 21.47% returns in 2017, with the Dunn WMA Institutional UCITS, with $312 under management, delivering 10.92% — both meaningfully higher than managed futures category averages.

Dunn’s WMA fund trend following program, with more than $1 billion in total assets, was among the HSBC top 20 performers and witnessed significant success in the last three months of the year, according to Niels Kaastrup-Larsen, Managing Director of DUNN Capital Europe and host of the podcast Top Traders Unplugged.

He credit’s Dunn’s outperformance to “improvements” they made to their trend following models and sticking to what they know best. He points to strong performance when market environments were generally challenging during March and lasting into the summer of 2017, a point where they “defended” their profits, but then delivered significant benchmark outperformance in the fourth quarter, largely on the back of a combination of long equity positions along with long and short gains in the energy complex. The fund does this “without any fancy machine learning techniques,” a hot-button topic among Managed Futures practitioners.

Their performance contrasts that of Man AHL. Man is the first known traditional CTA strategy practitioners to claim profitability on a machine learning strategy. The $3.4 billion Man AHL Evolution fund, managed in London by Tim Wong and Matthew Sargaison, was up 18.2% in 2017. The exact performance attribution to “machine learning” or how that is specifically defined is unknown, but the firm is known to have been working on numerous algorithmic changes in 2017.

This article was originally published in ValueWalk.

Photo: Ivan T

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