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Computer-driven trading raises meltdown fears
Analysts estimate that up to 60 per cent of trading in equity markets is driven in this way.
Trading in equities and derivatives is being driven increasingly by mathematical algorithms used in computer programs. They allow trading to take place automatically in response to market data and news, deciding when and how much to trade similar to the autopilot function in aircraft.
Concerns have been highlighted by news that NYSE Euronext, the transatlantic exchange operator, has fined Credit Suisse proprietary trading arm for the first time for failing to control its trading algorithms. In the Credit Suisse case, its system bombarded the NYSE’s systems with hundreds of thousands of “erroneous messages” in 2007, slowing down trading in 975 shares.
The case was far from isolated, say traders. CME Group, the Chicago-based futures exchange, is investigating a case this month where a trader in “mini” S&P Index futures contracts “inadvertently traded approximately 200,000 contracts as both buyer and seller”.
EDITOR’S CHOICE
FT Trading Room: Exchanges news and analysis - Sep-09
Lombard: Man Group; Qinetiq; M&B - Jan-15
Last year, the London Stock Exchange suffered a three-hour outage after its trading system collapsed under the strain of a huge volume of orders. Some traders blamed the spike in volumes from algorithmic trading.
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A final version of the second law was put to rhyme by Flanders and Swann[3], based on the Clausius statement:
Heat won't pass from a cooler to a hotter
You can try it if you like but you far better notter
'cos the cold in the cooler will get hotter as a ruler
'cos the hotter body's heat will pass to the cooler!
Taleb also has another major problem with computers that has nothing to do with their uses and abuses in banking. From Taleb's perspective, computers have made the whole of the modern economy too complex and too efficient. From inventory management systems that ensure that retail outlets hold the optimal amount of inventory (no less and no more) for a given day and location, to the massive options pricing machines that time trades with millisecond precision, the entirety of the computer-driven global economy is like one massive model that was assembled—most of it over the course of the past decade—on the governing assumption that the future would look pretty much like the past. And when that widely shared assumption breaks down, then the system ceases to behave in a predictable way, because it has been too finely tuned to operate under a set of parameters that no longer pertain