11 years ago this week, The Economist released a story explaining how algorithmic trading is becoming far more sophisticated for institutions. At the time, robo-traders were helping firms to increase speed, process more data, reduce human error, and reduce payroll. The benefits institutions received from algorithmic trading years ago have finally become available for self-directed traders. This article is both nostalgic for some and timely for others.
Software: Programs that buy and sell shares are becoming ever more sophisticated. Might they replace human traders?
IMAGINE the software equivalent of a golden goose: a program that continually produces money as its output. It sounds fanciful, but such software exists. Indeed, if you have a pension or endowment policy, or have money invested in share-based funds, the chances are that such a program—variously known as an “autonomous trading agent”, “algorithmic trading” system or simply as a “robo-trader”—has already been used to help your investments grow.
Simple software-based traders have been around for many years, but they are now becoming far more sophisticated, and make trades worth tens of billions of dollars, euros and pounds every day. They are proving so successful that in the equity markets, where they are used to buy and sell shares, they already appear to be outperforming their human counterparts, and it now seems likely that their success will be repeated in foreign-exchange markets too. Proponents of robo-traders claim that, as well as making more money, they can also help to make markets more stable. And, of course, being made of software, they do not demand lunch breaks, holidays or bonuses.
This has prompted an arms race as companies compete to develop the best sets of rules, or algorithms, to govern the behaviour of their robo-traders. “We live and die by how well they perform,” says Richard Balarkas, global head of advanced execution services at Credit Suisse First Boston, an investment bank. The better the technology, the more money it makes for the client, he says.
At the moment, big strategic decisions, such as deciding which shares to buy and sell, are still made by experienced human traders, says David Cliff, who is the director of Deutsche Bank’s Complex Risk Group in London and a veteran of the field. Robo-traders are then given the power to decide how to buy or sell shares, always with the aim of hiding their client’s intentions. If you are a pension-fund manager and have decided to sell a million shares in some company, merely revealing your intention to sell will result in the market moving against you, even with very actively traded shares, notes Dr Cliff. So the aim of the game is to try to unload the shares in such a way that no one notices what you are doing.
Buy! Sell! Exterminate!
The simplest algorithmic-trading systems might try to drip-feed the market by slicing up a big trade into a hundred smaller orders. By introducing these trades slowly into the market over some predetermined period of time—a few minutes, or hours, or days—the idea is that the smaller orders are less noticeable, and so have a less dramatic effect on the market price. But such “salami slicers” would not win any prizes these days, says Dr Cliff. Today’s more advanced robo-trading programs can cover their tracks more adeptly, for example, by varying the amount they sell, and sometimes even buying back the very stock they are trying to get rid of, he says.
Read the entire article at: The march of the robo-tradersTweet Follow @AltaFive