Hedge funds are on their way to become the next big thing in investment management. New funds start up every day, hedge funds are marketed aggressively to institutions and, under pressure to make up for recent losses, many institutional investors are showing serious interest. Many investors do not seem to realise, however, how much more complex hedge funds are compared to stocks and bonds. Over the past 20 years, under the influence of ‘modern’ portfolio theory, investors have come to approach investment decision-making in an increasingly mechanical manner. Mean-variance optimisers are filled up with historical return data and the optimal portfolio allocation follows. With hedge funds such an approach can be extremely misleading, however, as it will cause investors to overlook a number of very important issues. As a result, investors will see miracles where there are in fact none. In this brief note we discuss this matter in some more detail.
Hedge fund return data contain a number of biases which make hedge fund performance over the last 10 years look a lot better than it really is. Research has shown that when not correcting for the fact that hedge fund databases tend to be backfilled and only provide information on funds that have survived over the years investors will overestimate the average return on hedge funds by 4-5% per annum.
In addition, accurate marking-to-market of hedge fund portfolios can often be problematic due to the illiquid nature of many funds’ investments. This causes artificial lags in the evolution of hedge funds’ net asset values, which in turn may lead to substantial underestimation of hedge fund volatility, sometimes by as much as 30-40% or even more.
Another problem arises from the fact that the available data on hedge funds span a very short and unique period: the bull market of the 1990s and the various crises that followed combined with the spectacular growth of the hedge fund industry itself. This sharply contrasts with the situation for stocks and bonds, for which we have data available over many business cycles. This has allowed us to gain insight into the main factors behind stock and bond returns and allows us to distinguish between normal and abnormal market behaviour. The return generating process behind hedge funds on the other hand is still very much a mystery and so far we have little idea what constitutes normal behaviour and what not. In addition, we have little idea when the hedge fund industry will reach capacity. With the growth of the industry, hedge fund returns have tended to come down every year. This could be an indication that there are no longer enough opportunities in the global capital markets to allow hedge funds to continue to deliver the sort of returns that we have seen so far.
Importance of skewness
A second reason why many investors think hedge funds are less risky than they really are stems from the use of the standard deviation as the sole measure of risk. The returns on portfolios of stocks and bonds are more or less normally distributed. Because normal distributions are fully described by their mean and standard deviation, the risk of such portfolios can indeed be measured with one number. Confronted with non-normal distributions, however, it is no longer appropriate to use the standard deviation as the sole measure of risk. In that case investors should also look at the degree of symmetry of the distribution, as measured by its so-called ‘skewness’, for example. Research has shown that hedge fund returns exhibit relatively low standard deviations but at the same time provide skewness attributes that are exactly opposite to what investors desire. It is this package which constitutes hedge fund risk, not just the standard deviation.
Given their relatively weak correlation with other asset classes, hedge funds can play an important role in risk reduction and yield enhancement strategies. This diversification service does not come for free, however. Although the inclusion of hedge funds in a portfolio may significantly improve that portfolio’s mean-variance characteristics, it can also be expected to lead to significantly less attractive skewness characteristics as when things go wrong in the stock market they also tend to go wrong for hedge funds. Not necessarily because of what happens to stock prices (after all, many hedge funds do not invest in equity), but because a significant drop in stock prices will often be accompanied by a widening of credit spreads, a significant drop in market liquidity, higher volatility, etc. The 2002 experience provides a clear example of this.
Shortcomings of mean-variance analysis
Since it only looks at the variance of the return distribution, mean-variance analysis of course completely skips over the above skewness phenomenon. In the same way, mean-variance analysis also skips over the low liquidity and increased parameter uncertainty of hedge funds. When bringing together different assets or asset classes in a mean-variance framework we implicitly assume that these are comparable in terms of liquidity and the quality of the inputs used. With stocks and bonds this assumption is often justified. When alternative investments are introduced, however, this is no longer true. Many hedge funds employ long lock-up and advance notice periods. In addition, without more insight in the way in which hedge funds generate their returns it is very hard to say something sensible about hedge funds’ future longer-run performance. This illiquidity and additional uncertainty should be properly incorporated in the portfolio optimisation process. If not, hedge funds are artificially made to look good and consequently too much money will be allocated to them.
Unlike what many investors like to believe, there are no shortcuts in hedge fund selection. After properly controlling for the risks involved, small funds do not outperform larger funds, young funds do not outperform older funds, closed funds do not outperform open funds, etc. In addition, research has shown that there is no persistence in hedge fund track records, ie, this year’s performance says nothing about next year’s. Proper hedge fund selection is therefore first and foremost about asking the right questions and doing one’s homework. Due diligence question lists can be helpful as long as getting all the questions answered does not become more important than correctly interpreting the answers. When setting up a due diligence procedure, investors must remember that the most important goal is to obtain insight in the true risk-return profile of the fund in question. This means asking a lot of detailed questions about the strategy and risk management procedures followed and studying the latter under many different scenarios. In this context, transparency is of course an extremely valuable asset.
Hedge fund investing is not without pitfalls. Data should be corrected for various types of biases. Standard mean-variance analysis only looks at (the good) part of the hedge fund story, while ignoring skewness, liquidity and parameter uncertainty.
Funds selection is (and probably always will be) more art than science. Since the academic tools to deal with these issues are not there, proper hedge fund investing heavily relies on good old-fashioned common sense, asking the right questions and doing one’s homework. Hedge funds offer investors a way to obtain a lower standard deviation and/ or higher expected return but at a definite cost. Whether the resulting portfolio makes for a more attractive investment than the original is a matter of taste, not a general rule!
Harry Kat is professor of risk management and director at the Alternative Investment Research Centre Cass Business School, City University in London