Marc Defilippi, senior portfolio manager at the fund of hedge fund business EIM, takes a look at the use of passive investment vehicles in dynamic asset allocation approaches.

Passive investing using ETFs (exchange-traded funds) or other trackers has gained popularity among the investor community over the recent years. While long term investors are meant to keep their allocations untouched, the significant draw-downs exhibited by equity markets has made such a strategy untenable for many portfolios.
 
As assets dwindle in the face of losses, fiduciaries question the wisdom of keeping such a risky allocation, or regulators force actions to minimise further deteriorations of the asset liability gap. However, it has been shown that using ETFs in the context of a more active and dynamic asset allocation can be very effective in limiting draw-downs and can generate value across a liquid investment universe, whether alternative or traditional.
 
Following the credit crisis, many investors have not only been disappointed by the performance of their hedge fund exposure but also by the impossibility of being able to redeem their investment. Investors were forced to continue holding illiquid positions (sidepockets) within their portfolio, unless they were prepared to dispose of them at a steep discount through the secondary market.
 
Since then, the quest for liquidity, especially by private investors, hasn’t abated. Interestingly, liquid strategies such as CTAs (commodity trading advisors) were able to hold up during the crisis (The HFRX Systematic Diversified Index returned +31 per cent in 2008). However, the following year CTAs lost 9 per cent on average while other hedge fund strategies outperformed. Experience shows that hedge fund strategies have their own cycles and behave differently depending on the market environment.
 
As a clear sign of the continued institutionalisation of the fund of hedge fund industry, the bulk of its total investment performance is explained by allocation decisions, as had already been proven to be the case for traditional assets by Brinson in the mid-80s. For sure, selecting best of breed hedge fund managers is important. However, identifying the best individual talents has become more difficult over the years and the incremental added value has diminished over time in relation to the impact of being in the strategies most adapted to the environment. With passive investments, of course, the question of value-added from selection is irrelevant as vehicles are designed to perform as the index it replicates minus limited costs.
 
Demand for liquidity and the cyclical behavior of hedge fund strategies has motivated EIM to search for innovative solutions within the multi-manager area. Based on our exhaustive qualitative, operational and quantitative due diligence experience, EIM devised a quantitative fund ranking and selection model which it first applied to a universe of hedge funds offering weekly liquidity.
 
While traditional quantitative selection tools focus on return and volatility, EIM’s model - called Systematic Dynamic Allocator, or SDA - also uses criteria which take into account market dependence and each hedge fund’s ability to diversify various traditional asset classes. This broader assessment of manager behaviour allows a systematic selection of managers based on the likelihood that they will perform in the current market environment. By allowing strategy allocation to fall out from this bottom-up assessment of manager suitability, the resulting strategy allocation has proven to be extremely dynamic and flexible and has protected against losses during prior periods of market stress.
 
For instance, while the HFRX Global Hedge Fund Index lost more than 23 per cent in 2008, the SDA model’s pro forma results show that it was able to limit its losses to 5 per cent. The model anticipated the crisis by increasing its allocation to CTA managers starting in summer 2007 and then reduced this exposure from its peak before the strategy’s subsequent decline. The same occurred with convertible arbitrage managers which were rapidly increased in spring 2009 after having been crushed late 2008.
 
The compelling allocation features of the SDA concept when applied to a universe of liquid hedge fund led EIM to explore whether or not it could also successfully add value in traditional asset classes. Indeed, results were equally promising. In fact, we determined that adding cash instruments to the allocation universe, along with equity, commodities and fixed income vehicles, allowed the model to very efficiently protect capital during times of crisis or bear markets. The multi-asset version of the SDA-model allocated around 80 per cent to cash before the Lehman default, resulting in a limited loss of -6.9 per cent in 2008.  Conversely, from April 2009, the SDA-model, reduced cash to zero. Very few investors were able to allocate risk back into markets that early after a sell off that ended in early March.
 
As we have seen, the use of passive investment vehicles combined with passive asset allocation leads to downside risks that are not sustainable for many investors, but the liquidity and breadth offered by these instruments lends itself to a dynamic asset allocation process. The question remains, however, as to whether a discretionary or a systematic approach would be most likely to generate the best active allocation results over time. One might assume that the two methods will generate very similar results if they are based on the same well-defined set of decision-making rules and criteria, but in reality, the results are very different.

As an analogy, consider driving. Rules and criteria are clear, and are manifested by road markings, speed limits and traffic lights. Drivers, however, are by definition discretionary agents, whose decisions are influenced by exogenous factors such as stress and impatience, just as greed, fear and herd behaviour influence the judgment of a discretionary trader.
 
Systematic approaches allow for a rational, controlled, rigorous and detailed study of system characteristics, and for the dispassionate elaboration of decision rules. These can then be applied systematically, without emotion, and should therefore deliver better results within a changing environment, as the model’s adaptation to new conditions will not be slowed by fear, nor overshoot due to enthusiasm or greed, but can dynamically capitalise on opportunities as they arise.