The Flash Crash

Last May 6, the Dow Jones Industrial Average made a rapid series of inexplicable drops, and, in fact, in one five-minute period fell more than 500 points.  Then, just as inexplicably, the market recovered.  The causes of the so-called Flash Crash remained mysterious until September, when the SEC issued a report on the rapid fluctuation of the market.  It found that a single "large fundamental trader" had used an algorithm to aggressively hedge its market position quickly.
Since then the role of neural networks and algorithms in automated transactions has received a good deal of attention from the media.  The online edition of this month’s Wired offers a fascinating perspective on algorithms as investors.  It reveals how neural networks and other automated types of statistical analysis  can chew through news of the financial markets–essential a big pile of data– to instantaneously produce a financial risk analysis, make a larger determination of the results of a prospective trade portfolio risk management terms, and make the trade.  The speed with which a computer can function as an investor is part of the problem. It produces a kind of feedback loop in which each instantaneous trade produces instantaneous responses from other computers trolling the markets. 
The trend toward computer control of financial markets, however, does not continue unfettered. The month after the Flash Crash, the SEC instituted some "circuit breakers," rules to stop trading when the feedback loops begun too intense and the markets fluctuate too rapidly.

All of this presents an interesting and larger question: How much control can we delegate to computers–not just in the financial realm but in our social and creative lives–before we have to scramble to catch up with them and regain control?   

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