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April 24, 2013

How a phony tweet and computer trades sank stocks

NEW YORK — For a few surreal minutes, a mere 12 words on Twitter caused the world's mightiest stock market to tremble.

No sooner did hackers send a false Associated Press tweet reporting explosions at the White House on Tuesday than investors started dumping stocks — eventually unloading $134 billion worth.

Except most of the investors weren't human. They were computers, selling on autopilot beyond the control of humans, like a scene from a sci-fi horror film.

"Before you could blink, it was over," said Joe Saluzzi, co-founder of Themis Trading and an outspoken critic of high-speed computerized trading. "With people, you wouldn't have this type of reaction."

For decades, computers have been sorting through data and news to help investment funds decide whether to buy or sell. But that's old school. Now "algorithmic" trading programs sift through data, news, even tweets, and execute trades by themselves in fractions of a second, without slowpoke humans getting in the way. More than half of stock trading every day is done this way.

Markets quickly recovered after Tuesday's plunge. But the incident rattled traders and highlighted the danger of handing control to the machines. It also raised questions about whether regulators should be doing more to monitor the relationship between social media and the markets.

Irene Aldridge, a consultant to hedge funds on algorithmic programs, said many of the trading systems just count the number of positive and negative words, without any filter. She wants regulators to do more but believes that glitches and plunges may be inevitable.

"You can't ban Twitter," said Aldridge, author of "High-Frequency Trading," a guide to algorithmic trading.

Just how exactly the trading unfolded Tuesday is still a bit of a mystery.

Some experts say the computers took their cue from humans, picking up on a pause in buying as traders read the phony tweet. In Wall Street's insanely fast trading world, humans holding back for even a second could have signaled to computers that buyers were drying up and that prices could fall, and so the computers should sell fast.

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