Of course in reality, as most hedge fund investors know, quantitative managers operate highly disciplined and diversified investment processes. However, there is a vast range of strategies ‘bucketed’ into the Quant category with some popular misconceptions applied across the board. Essentially, there are two main equity quant hedge fund approaches; statistical arbitrage – trading strategies that started life in the investment banks’ proprietary trading divisions and fundamental factor-based strategies – more typically employed by the large asset managers. These two strategies are not mutually exclusive and, in fact, if both are combined to an optimal level, a consistent return series is exhibited with possibly less expected contribution in extreme market volatility spikes but, achieving a far greater return series over a cycle as many more opportunities for profit in most market environments are generated.
Statistical arbitrage means reverting strategies tend to be greater return contributors in times of higher volatility and can therefore provide portfolio insurance. However, they can underperform when factors are trending. Traditional static factor strategies tend to perform strongly in rational markets and particularly when investors are focusing on value and momentum-based themes. However, these strategies struggle to achieve returns when crowding occurs.
A 21st Century generation of factor strategies, however, have additional degrees of freedom and can capture returns from being both long and short factor exposures over a variety of different time horizons. These dynamic strategies are paid by collecting the premia due to the longer term economic cycling effects and the premia due to shorter term behavioural effects. Incorporating contrarian strategies into the optimised selection of dynamic factor bets enhances the overall robustness of the strategy and provides downside protection at inflection points. Thus, these strategies aim to be ‘all weather quant funds’. So quantitative strategies are clearly not all the same. Some are designed with higher risk appetites in mind and others are constructed to appeal to those with a more institutional investment requirement ie. consistent returns with low annualised volatility. Some strategies are highly complex, some are reasonably transparent and some have elements of both attributes. Keeping it simple, as with any process, means that there is less to go wrong.
Mathematically designing a straightforward process to generate the best possible returns and being able to communicate that strategy to investors provides comfort as one is able to ‘see inside the box’. The further enrichment of the core strategy by incorporating additional intuitive models, developed from proprietary data capture, provides investors with the extra assurance of knowing that their chosen manager is not necessarily ploughing the same field as others.
Essentially, however, quantitative strategies do have one common aim; to maximise the accuracy of forecasting skill – getting a greater number of bets right, and in greater magnitude than those that are wrong.
During the last few years there has been significant growth in the size of assets managed quantitatively in long only products, ‘hybrid’ or 13030 strategies and, of course, hedge funds. Many argue that this is what led to the contagion effectin August of 2007 – so many managers pursuing value and momentum-based methodologies.
So what should investors be looking for in quant strategies going forward?
Sabre’s Style Arbitrage strategy was the first dynamic factor strategy in Europe when it was introduced in mid 2002. Sabre’s dynamic factor strategies have generated 14.18% and 18.73% in 2008. Since inception, Sabre Style Arbitrage Fund Ltd has achieved its stated compound annualised return target of 6-8% over cash with a Sortino Ratio of 2.7 (for period from inception in Aug 02 to Mar 08.