Thanks primarily to hedge funds, alternative investment management has gained in visibility over recent years. Some alternative tools, such as short selling and leverage, are becoming increasingly widespread and it therefore comes as no surprise that the new European UCITS III directive authorizes their use in public funds. A traditional portfolio manager can now leverage the performance of his long-only strategy by short selling 30% of the value of the portfolio and investing the proceeds in additional securities. This enables him to build a portfolio with long positions for 130% of his initial capital and short positions for 30% of the same capital, which is why the fund is called a "130/30" fund.

 

These new strategies have much in common with more conventional long-only strategies. In particular, 130/30 portfolios hold positions that differ from the benchmark (they take active bets), and, as the 30% in short positions is offset by 30% in long positions, the corresponding market exposure is 100%. However, by relaxing the no-shorting constraint, 130/30 portfolio managers can more fully capture their negative views, can hedge their strategy against biases, whether industry, regional or style-related, and can structure portable alpha strategies.

 

A portfolio managed relative to the MSCI Europe Index provides a good example. There are 582 stocks in the index, 377 of which have a weighting below 0.1%. A long-only manager who is expecting a decline in one of these stocks cannot underweight it by more than 0.1%; this therefore represents a major loss of opportunity.

 

The long-only constraint can also introduce unwanted biases. For example, imagine that a manager wants to overweight several small-cap stocks. Given that it is impossible to underweight the other stocks by more than their weight in the index, this strategy will implicitly produce a small-cap bias. The manager therefore faces a choice: either he has to accept this portfolio bias or he has to go without this source of alpha.

 

 

The capacity to translate pure stock selection expertise into the portfolio is therefore at the heart of the problem. Research on this capacity – measured by the transfer coefficient – shows that the long-only constraint reduces the alpha present in the pure – and unconstrained – stock-picking phase. When optimized funds are managed relative to a benchmark, the efficient frontier – which plots return against risk – tends to flatten beyond a certain level of risk. Beyond this level, taking on more risk adds scarcely any value. But as soon as the long-only constraint is relaxed, the efficient frontier steepens and it becomes possible to obtain higher alpha by assuming slightly more risk. Efficiency can therefore be improved by relaxing the short-selling constraint. In the case of portfolios managed relative to an index, it is valid to ask up to what point this applies, bearing in mind that UCITS III authorizes long-short exposure of up to 200/100. The answer, although specific to each management process, is influenced by three factors.

 

The first relates to the chosen level of risk, or, in this case, tracking error. The higher the risk, the more the fund manager needs to relax the no-shorting constraint in order to generate alpha and so obtain an attractive risk/return ratio.

 

The second is the fund manager’s profile. A manager who specializes in seeking out overvalued stocks will benefit more from the possibility of selling short, particularly if these overvalued stocks are not large caps. A manager with forecasts on a large number of stocks will also be able to take advantage of the relaxation of the constraint to optimize his portfolio. In contrast, a long-only manager taking large bets on a small number of stocks will be forced to underweight several stocks for which he does not have any forecasts so as to stay within his risk budget or generate the capital needed to leverage his long bets.

 

The third factor is the level of market volatility and the dispersion of the stocks’ returns. In a low-volatility environment, such as we until recently experienced, managers are forced to take larger active bets to generate performance. The size of their short positions is therefore also proportionally higher.

 

In this regard, it only takes a few simulations to show that the 130/30 structure offers an excellent compromise between risk and return, and also that a dynamic approach can be wise. In any case, there is a consensus among investors that, beyond a certain limit, funds fall into the hedge fund universe and, more precisely, they should be classified as long-short hedge funds.

 

So are 130/30 funds all they are cracked up to be? We would say yes they are, but the substantial efficiency gains are achieved at the cost of operational complexity and higher risk.
 
Indeed, behind the asymmetry between the market risk of a long position and a short position a number of pitfalls are hidden, e.g., differences in the behavior of falling and rising stocks, the mark-to-market valuation of any losses and related margin calls, the management of collateral, issues relating to the availability of stocks for short selling, costs at the mercy of supply and demand, and possible stock recalls, to name just a few, in no particular order. On the operational side, the fund manager also has to develop more sophisticated infrastructure and logistics. Under UCITS III, implementation can be simplified by means of a swap exchanging with a counterparty the performance of the strategy for the financing costs of the structure. The counterparty therefore partially assumes the prime broker role so well known in the hedge fund industry. But although this solution means the fund manager is able to draw on the expertise of an experienced investment bank, it still initially involves a complicated but vital process of counterparty selection.

 

A wide skill set and a high degree of technical know-how are therefore essential for leveraging alpha.

 

 

It is not therefore surprising that most of the first 130/30 funds to have appeared on the market are run by quantitative managers. Lombard Odier Darier Hentsch & Cie’s quantitative management model produces forecasts for all stocks in the benchmark and therefore naturally generates many ideas for shorting. The large number of forecasts then allows us to build a highly diversified portfolio that makes optimal use of the relaxation of the no-shorting constraint. To this end, we have access to a proprietary optimization tool that allows us to penalize positions that are difficult or expensive to borrow.

 

Thanks to this broad diversification of ideas, we are able to make sure we do not have significant exposure to a stock likely to suffer a short squeeze. Our ability to manage all these specific features insures that we are well equipped for a more "alternative" management approach.

 

Dr Yannik Zufferey, quantitative management specialist