The Kellogg team tapped into more than 2 million instant messages sent between 2007-2009 by financial traders buying and selling stocks in that hugely violatile time period.
"The more the instant messages came in waves—different from what would be expected if the IMs were sent and received randomly, as in casual conversations—the more synchronous trading became. And the higher the traders' synchrony, the more likely they were to dodge losses," Physorg.com explains.
The more a trader buys and sells in sync with others, the better their performance. Instant messaging, which is part of most traders' daily routines, helps traders observe the individual responses of other traders.
"The reason sync is thought to exist is that any single animal on its own cannot process the complex information they're sometimes faced with. So when complexity increases, the animals appear to manage it better with a collective response that emerges from their individual responses, even though they are not trying to coordinate," Brian Uzzi, a professor of management and organizations at the Kellogg School and one of the papers authors, tells Physorg. “We've seen this in nature and we were excited about the prospect of it happening in human systems.”
Instant messaging is performing some of the same tasks as market prices—conveying dispersed information about the world to traders. It may allow traders to process the information faster than it can be priced into the market.
"For a long time we've known that people trade stocks based on information," Phsyorg quotes Kathleen Hagerty, a professor of finance at the Kellogg School and another author of the paper, as explaining. "If big news comes along, like a blown-up refinery in Libya, there's a good chance people will trade on it. But its not like they just read the news and press buy or sell. The time to trade is after they're fairly sure about what the news means to their stock, but before other people move on it."
Trading volume increased as IM volume increased—and slowed as IM volume slowed. Fascinatingly, this wasn't a case of herding—traders piling in on the same trades. The individuals trading during the same time interval typically dealt with unrelated stocks.
CNBCs Kate Kelly recently reported a series on the effects of Twitter on trading. While the Kellogg study didnt cover Twitter, its easy to see that as more traders come to use it, it could have effects as powerful—or even more powerful—than the Kellogg authors discovered with instant messaging.
A study published last fall suggested that the collective mood of Twitter—as measured by millions of random daily tweets—could predict with 87 percent accuracy how the Dow would move on any given day, up to four days before it actually happened.
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