What's it all about, alpha?

Mar 22nd 2007
From The Economist print edition

Demystifying fund managers' returns


TOO many notes. That's what Emperor Joseph II famously said to Mozart on seeing his opera “The Marriage of Figaro”. But surely to think of a musical work as just a series of notes is to miss the magic.

Could the same be said about fund management? It is the fashion these days to separate beta (the systematic return delivered by the market) from alpha (the manager's skill). Investors are happy to pay high fees for the skill, but regard the market return as a commodity. Distinguishing the two is, however, difficult.

A fund manager might beat the market because of luck or recklessness, rather than skill, for example. Suppose he packed his portfolio with oil stocks. When the crude price rises that would pay off, but it would be a pretty risky portfolio. More generally, alpha sceptics often attribute eye-catching returns to “style bias”, such as favouring stocks with a high dividend yield.

But should they be biased against style bias? After all, the only portfolio utterly free of bias would be one that included the entire market. Were a Britain portfolio to exclude just one stock, such as BP, it would have a small-cap bias, a sector bias and a currency bias (most of BP's revenue is in dollars). Hence any excess return must stem from some element of style.

Academics have entered this debate, trying to pin down the factors that drive a fund's performance. These might include the difference in returns between small-cap and large-cap stocks (fund managers tend to favour the former) or the level of credit spreads and so on. Bill Fung and Narayan Naik of London Business School have come up with a seven-factor model which, they say, can explain the bulk of hedge-fund performance. After allowing for these factors, the average fund of hedge funds has not produced any alpha in the past decade, except during the dotcom bubble.

This approach suggests the whole idea of alpha might be an illusion. Academics can explain most of it, and the only reason they cannot explain all of it is because they are not clever enough to think of the missing factors.

However, it is also possible to take the opposite tack. This type of analysis gives managers no credit for choosing the systematic factors—the betas—that drive their portfolios. Yes, these betas could often have been bought for very low fees. But would an investor have been able to put them together in the right combination?

It is as if a diner in Gordon Ramsay's restaurants were brave enough to tell the irascible chef: “This meal was delicious. But chemical analysis shows it is 65% chicken, 20% carrot, 10% flour and 5% milk. I could have bought those ingredients for £1.50. Why should I pay £20?” The chef's reply, shorn of its expletives, might be: “The secret is in the mixing.

This debate matters because people are now trying to replicate the performance of hedge funds with cloned portfolios. Indeed Messrs Fung and Naik have shown that their model would have produced an annual return over the past four years of 11.6%, well ahead of the average fund of hedge funds. Their performance was purely theoretical. But Goldman Sachs and Merrill Lynch have launched cloned hedge funds on the market.

There are two potential criticisms of the cloned approach. One is that it will simply reproduce all the systematic returns that hedge funds generate and none of their idiosyncratic magic. However, this “magic” is hard to pin down. Even if it does exist, Messrs Fung and Naik suggest it may be worth no more than the fees hedge funds charge, so the managers are the only ones to benefit from their skills.

The second criticism is that the clones will always be a step behind the smart money. You cannot clone a hedge fund until you know where it has been. But by then it may have moved on. As a result, the clones may pile into assets that the hedge funds are selling, making the classic mistake of buying at the top. This may not be a fatal flaw, however. It is possible to imagine some clones taking contrary bets, buying the betas that seem temporarily out of favour, in the hope that they will be purchasing what the hedge funds are about to buy.

There are some nice ironies at work here. Hedge-fund managers often rely on secretive “black box” models: the investor puts his money in at one end and sees the returns spat out at the other, but no more than that. Now, armed with just that information, academics are coming up with their own models, which almost match the hedge funds' performance.

Mozart might have sympathised. His operas were more than the sum of his notes. But even if the great composer had no peers, he has had plenty of imitators.


Goldman sets up hedge fund clone

By Steve Johnson

Published: December 3 2006 19:43 | Last updated: December 3 2006 19:43

Goldman Sachs has become the first bank to create a hedge fund replication tool in a move that could lead to a shake-up of the $1,300bn hedge fund industry.

The platform will greatly undercut the notoriously high fees of the hedge fund sector. Those investing through a fund of funds can end up paying annual charges of 4-7 per cent, with up to 50 per cent of their returns eaten up by fees. Goldman will charge a flat 1 per cent.

Goldman’s Absolute Return Tracker index (Art), is set to be among the first of a flood of hedge fund cloning products likely to be launched in a revolution being compared with the arrival of index trackers in the mutual fund world a generation ago. “There is a lot of dead wood in the industry – people who should not be running hedge funds,” said Harry Kat, professor of risk management at London’s Cass Business School, who has just launched his own hedge fund replication tool.

“A lot of them will leave the business, because people are smartening up. Index replication is going to become as important as it is in traditional long-only investment, with 30-40 per cent of the market.”

Replication strategies are based on academic research that suggests hedge fund performance is largely driven by movements in underlying markets, such as equity, bond and commodity prices, rather than the intrinsic skill of managers.

Goldman has spent two years developing the algorithm that underpins its platform. The performance characteristics of thousands of hedge funds will be fed into the system monthly and Art is designed to decompose these data and calculate the aggregate position of the hedge fund universe. This position can then be replicated, potentially allowing Goldman to generate hedge fund performance at a fraction of the cost.

Clones such as Art avoid the negative selection bias that bedevils existing investible hedge fund indices and funds of funds, due to the fact that few of the better hedge funds are open to new investment.

It will be far more liquid, with trading available on a daily basis.

“This may be ideal for any large institution that has been looking at hedge funds but doesn’t like the fact that it takes six months to put money [in] and to take it out again,” said Edgar Senior, executive director in Goldman’s fund derivatives structuring team.