Case for active style allocation
Al though the existing literature seems to concur on the interest of hedge funds as valuable investment alternatives, there seem to be several shortcomings in current industry practice when it comes to fully capitalising on the advantages of including hedge funds in an investor’s asset allocation.
So far, the only solution to gaining exposure to alternative investment strategies for most investors was to invest in multi-strategy funds of hedge funds. This solution, however, poses two problems. On the one hand, funds of hedge funds solutions are off-the-shelf products that are not designed to meet the specific needs of a specific investor.
On the other, the fact that funds of hedge funds still suffer from a significant lack of transparency and are affected by style biases and individual managers’ style shifts makes it extremely difficult for investors to properly optimise their overall allocation in a multi-factor environment.
In a recent research paper, we argue that a more mature way of enjoying the benefits of hedge funds is to use a customised portfolio of pure strategy indices, designed to let investors gain access to the benefits of active style allocation decisions.
To this end, we first show that a customised portfolio based on hedge fund strategy indices dramatically outperforms a one-size-fits-all solution in terms of diversification benefits, especially when higher order moments of asset return distributions are taken into account. For the sake of illustration, we conduct a numerical experiment from the standpoint of a specific investor with a given initial asset allocation, eg, 20% in stocks and 80% in bonds.
We further assume that the investor is willing to allocate as much as 15% to hedge funds and design the optimal allocation to various hedge fund strategies so as to minimise the resulting portfolio value-at-risk.
To assess the benefits provided by the hedge fund portfolio in terms of both average and extreme risk diversification, we compute the decrease in volatility and in modified value-at-risk it entails over the out-of-sample sample period (ie, from January 2000 through December 2004). As a means of comparison, we conducted the same experiment with both the S&P and CSFB/Tremont composite indices. We also use the Edhec Funds of Hedge Fund index as a proxy for a typical investment in hedge funds.
As can be seen from the chart Diversification benefits, normal and extreme risks are reduced by 10.8% and 16.4% (respectively 10.8% and 15.6%), when traditional asset classes are mixed with the composite hedge fund index provided by S&P (respectively CSFB/Tremont).
When traditional asset classes are mixed with our optimally designed portfolio, the benefits in terms of normal and extreme risks are estimated to be a reduction of 17.7% and 22.7% respectively. In other words, using optimally designed portfolios instead of off-the-shelf products generates a diversification effect on normal and extreme risks that is on average 64% and 42% higher. The benefits of our approach are even more striking when compared to the reduction in normal and extreme risks achieved by the introduction of the fund of hedge fund index.
An added advantage of style indices is that they allow investors to perform style timing, ie, dynamically change their allocation to various hedge fund strategies in response to changes in their expectations about expected returns on these strategies.
To illustrate how the benefits of active style rotation can be added to the benefits of diversification to ensure the design of an even better investment solution, we further show that investors can use a robust multi-factor approach combined with a robust Bayesian optimisation approach inspired by the Black-Litterman model to dynamically change their allocation to various hedge fund strategies in response to changes in their expectations about future returns on these strategies.
The Black-Litterman model is a formal optimisation process based on the desire to combine neutral views consistent with market equilibrium and individual active views.
The model uses as inputs confidence levels on investors’ active views and generates final estimates of expected return that incorporate both market views and individual expectations based on a Bayesian approach. While the model is well-suited for portfolio construction in the context of active asset allocation decisions, it suffers from an important limitation, namely, it relies on volatility as the definition of risk. For the purpose of our numerical experiment on the benefits of hedge fund style timing, we first extend the Black-Litterman model by taking extreme risks, so that the focus on volatility is replaced by a focus on value-at-risk as the proper measure for risk.
The table presents summary statistics for three corresponding portfolios designed from an active style selection process based on multifactor lagged analysis, combined with the Black-Litterman portfolio selection method. These results show that active style timing allows for significant out-performance without a large increase in tracking error with respect to the benchmark (taken to be the strategic style allocation portfolio from the previous numerical exercise).
We have presented evidence that existing investment in hedge fund portfolios, typically done through multi-strategy funds of hedge funds based on the selection of high performance funds, does not allow investors to access the full benefits of active allocation in the hedge fund universe. Given the low allocation typically made to alternative investment strategies (ie, generally 5-15% of the global allocation), investors must try to maximise the benefits of their hedge fund portfolios. We have shown that this can be done by customising an optimal hedge fund portfolio and by taking into account the investor’s original allocation to stocks and bonds. Overall our results strongly suggest that significant value can be added in a hedge fund portfolio through the systematic implementation of active style allocation decisions.
This conclusion seriously calls into question the traditional approach of investing in hedge funds via multi-strategy funds. It justifies turning to allocations that are based on investable indices or funds of funds by strategy.
Professor Lionel Martellini is the scientific director of the Edhec Risk and Asset Management Research Centre