Are ‘quant funds’ to blame for volatility?

Among the many culprits being blamed for the current turbulence in the markets are the 'quant' funds which take their cue to buy or sell from computer programmes rather than people. Tim Bennett looks at what they mean for your investments.

Among the many culprits being blamed for recent market turmoil are the vast quant' funds that take their cue to buy or sell shares from computer programs, rather than from people. But what are they, asks Tim Bennett, and what impact do they have on your investments?

Quantitative funds can be traced back to the early 1970s when Wells Fargo introduced an entirely computer-run mutual fund that tracked 1,500 stocks on the New York Stock Exchange. The newer equivalents also rely on computer programs for their trading instructions, using software that is the product of many hours of research by some of the cleverest mathematical minds in Wall Street and Canary Wharf. But for all their geeky sophistication, their basic trading strategies often vary little from those of a conventional, human fund manager. Some, for example, are long-only quants' that use screening tools to select the best stocks for a portfolio. Others are market-neutral', buying some shares and shorting others in an attempt to beat the market.

The more intriguing-sounding quant funds get involved in statistical arbitrage', where computer programs trawl hundreds of stocks trying to identify and exploit pricing anomalies. Arbitrage sounds grand, but it's often simple. For example, Nick Leeson made money legally for Barings early in his career by spotting that the Nikkei 225 futures contract traded at different prices simultaneously on the Simex and Osaka exchanges; the two used different trading methods, occasionally resulting in slightly different prices for the same contract. He would buy the contract on whichever exchange offered the lowest price, and sell it straight on to the other at a higher price, banking the small difference as profit.

Quant funds tend to keep their exact strategies top secret in a so-called black box', but all share a fondness for gearing borrowing big multiples of the fund's own capital in order to invest. So for every £1 contributed by one of its investors, another £5 of borrowed cash might be thrown at the fund's chosen strategy on top of this. This is because the price differences they are trying to exploit are often very small Long Term Capital Management once described it as "hoovering up nickels" so you only make decent money by investing frequently and in large amounts.

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This also mean the funds are huge. Some reckon that up to 50% of recent equity trading can be traced to stat arb' funds and Lehman Brothers estimates, quoted in the FT, suggest quant funds may control up to $1,500bn globally. A big chunk of the market's recent volatility is blamed on quant funds.

Quant funds: why use a computer at all?

There are supposedly two main benefits. Firstly, the opportunity Nick Leeson spotted didn't last forever as other people copied the trade, and so the gap between the two prices for the Nikkei 225 closed. In today's financial markets, where information travels at lightning speed, this can happen very quickly sometimes in a matter of seconds. Thus to find and exploit opportunities requires powerful programs capable of reading and analysing huge amounts of past share data and then reacting by placing bets much faster and more frequently than a human trader could.

Secondly, computers do not make errors of judgement there is no emotion in the investment process', as Charles Schwab put it. All investment decisions are down to a set of supposedly brilliant programmed assumptions undiluted by the whims of a fund manager. And unlike the rest of us, the black box can think' and trade 24 hours a day.

Quant funds: so what's the problem?

Basically a lot of quant strategies are backfiring after the recent market volatility triggered by the US subprime meltdown. This month Goldman Sachs attributed $3bn of losses to quant-driven hedge-fund activity. Its multi-strategy Global Alpha Fund is down 27% this year, says the FT. There are rumours that countless other quant funds are in trouble and selling assets to meet margin calls and fund losses.

There are two problems with these funds. The sheer size and frequency of trades is thought to have exacerbated recent market volatility quants have been dumping huge volumes of shares to cover losses on portfolios invested in high-risk assets. Secondly, in a throw-back to the Long Term Capital Management crisis in 1998 there seems to have been a failure on the part of programmers adequately to assess risk. Goldman Sachs chief financial officer David Vinier, trying to defend the bank's recent fund losses, described the latest gyrations in the equity and bond markets as 25 standard deviation events'.

In everyday English, this means he believes there was a roughly one in 244 million chance of them occurring. Yet clearly, crashes happen far more frequently than that. A more likely explanation is that even clever programmers sometimes get assumptions wrong and forget that the past which these funds rely on entirely is not always a guide to the future. Their creations are now being blamed for simply carrying out an ultimately human and flawed set of instructions.

Quant funds: what does this mean for me?

The good news for equity investors with steady nerves is that the indiscriminate selling of perfectly sound companies by these funds may present great buying opportunities once the market calms down. Many commodity stocks, such as BHP Billiton (LSE:BLT), Shell (RDS) and Rio Tinto (LSE:RIO) look even better value at these levels, given that global demand for metals and oil is unlikely to be dented by the current turmoil. To sum up, stay calm and shop selectively, and you could turn the City's programming mistakes into profits.

Tim graduated with a history degree from Cambridge University in 1989 and, after a year of travelling, joined the financial services firm Ernst and Young in 1990, qualifying as a chartered accountant in 1994.

He then moved into financial markets training, designing and running a variety of courses at graduate level and beyond for a range of organisations including the Securities and Investment Institute and UBS. He joined MoneyWeek in 2007.