Why humans are better than computers at making money
The chaotic and emotional nature of financial markets means they are virtually impossible to predict with computers, says Matthew Lynn.
Two years on from the start of the credit crunch and not a great deal has really changed. The banks have gone back to paying big bonuses, traders and dealers are as speculative as ever, and the hedge funds are still raking in fortunes. Still, one corner of the capital markets has been hammered hard the so-called 'quant funds'.
A few years back, the intellectually super-charged hedge funds that used mind-bogglingly complex formulas to trade assets and make huge profits for their owners were the hottest sector in the City and on Wall Street. But now the combined assets of the quant funds are down from around $1.2trn at the industry's peak to around $470bn now. That's a drop of more than 60%, according to data from the research firm eVestment Alliance. And around a quarter of the quant funds have closed in the last two years, according to figures from Lipper TASS. In part that tells us that investing styles go in and out of fashion. Sometimes people want gurus, sometimes charts, other times they want geopolitical trends, and so on. But it also tells us something more interesting.
Quants, as they became known in the markets, were obsessed with taking the human element out of their trading strategies. They scoured university campuses, taking astrophysicists and mathematicians blinking out of the library and paying them hundreds of thousands to have a shave, put on a suit (or at least some Boss chinos) and sit all day in an office on Mayfair's hedge-fund alley. Once installed, they came up with programs that could trade on tiny price discrepancies between different markets, and make a fortune from the results. Or they scoured the record books for past price relationships and built programs that could quickly exploit any change.
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But, although they had some big successes in the bull market, the quants were undone by the crash. None of the complex mathematical models they built predicted the credit crunch. All the expensive computer programs were about as useful as a bucket and spade in Birmingham. The quants' reputation were largely destroyed. The value of the funds fell so fast because they performed so poorly that disillusioned investors withdrew their money.
The fact is the markets remain impossible to mechanise. If you could build a program that predicted the markets, you would make, quite literally, billions. Yet no one ever manages it. Indeed, the harder they try, the worse the results usually are. In the 1990s, another hedge fund, Long Term Capital Management, which had more Nobel prize winners on board than Man City have expensive footballers, collapsed with vast losses and brought down the markets with it.
There are three reasons why the market remains so defiantly human and so resistant to smart mathematical models. First, they're chaotic. Computers are very good at capturing fairly straight-forward relationships, but equally bad at modelling complex ones. Chaos theory, according to which a butterfly can flap its wings in China and set off a chain reaction that causes a thunderstorm in Britain, provides one explanation. There are so many complex inputs making up the way weather works, you can't hope to capture them all. It's the same with the markets. Mortgagees default in Florida and a month later, the Royal Bank of Scotland is bust.
Secondly, computer programs are very bad at capturing human reactions and emotions. That's why they are good at chess, up to even a very advanced level, but not so good at bridge or poker. Those card games are based more heavily on reading an opponent's emotions to predict what they will do next. But the markets are much more like those card games than a strategic board game. Investment decisions, and hence the direction of the markets, are driven as much by emotion as anything else. Sentiment is strong some months, and weak in others, even if not very much really seems to have changed in the meantime. It is tough for any computer program to understand that, let alone model it and use it to make predictions.
Finally, behaviour changes. The way that investors behave and the markets respond evolves all the time. It isn't static, or predictable, like the way the moon revolves around the earth. It will be different today from yesterday, and different again tomorrow. The quant funds were building predictive models based on the way the market had behaved in the past. But just because a price has moved in a certain way historically does not mean it will move the same way in the future.
The lesson is a simple one. The markets will remain an arena for great traders with an instinctive feel for where asset prices are going. They can't be predicted with any kind of precision by computer programs, no matter how much brain-power has gone into creating them. Astrophysicists at hedge funds who for a few years could drive around in Porsches will return to the dusty poverty of the university library. Still, there is one comforting thought. You might find it fiendishly difficult to predict what any market will do in the next years but some of the smartest brains couldn't do it either.
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Matthew Lynn is a columnist for Bloomberg, and writes weekly commentary syndicated in papers such as the Daily Telegraph, Die Welt, the Sydney Morning Herald, the South China Morning Post and the Miami Herald. He is also an associate editor of Spectator Business, and a regular contributor to The Spectator. Before that, he worked for the business section of the Sunday Times for ten years.
He has written books on finance and financial topics, including Bust: Greece, The Euro and The Sovereign Debt Crisis and The Long Depression: The Slump of 2008 to 2031. Matthew is also the author of the Death Force series of military thrillers and the founder of Lume Books, an independent publisher.
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