Depending on how you look at it, this is either a harbinger of the emergent-model AI Singularity or a demonstration of the specious voodoo underpinnings of the automated financial markets… possibly both, if you’re a real pessimist [via Kottke.org].
A couple weeks ago, Huffington Post blogger Dan Mirvish noted a funny trend: when Anne Hathaway was in the news, Warren Buffett’s Berkshire Hathaway’s shares went up. He pointed to six dates going back to 2008 to show the correlation. Mirvish then suggested a mechanism to explain the trend: “automated, robotic trading programming are picking up the same chatter on the Internet about ‘Hathaway’ as the IMDb’s StarMeter, and they’re applying it to the stock market.”
Companies are trying to “correlate everything against everything,” [Bates] explained, and if they find something that they think will work time and again, they’ll try it out. The interesting, thing, though, is that it’s all statistics, removed from the real world. It’s not as if a hedge fund’s computers would spit the trading strategy as a sentence: “When Hathway news increases, buy Berkshire Hathaway.” In fact, traders won’t always know why their algorithms are doing what they’re doing. They just see that it’s found some correlation and it’s betting on Buffett’s company.
Now, generally the correlations are between some statistical indicator and a stock or industry. “Let’s say a new instrument comes to an exchange, you might suddenly notice that that an instrument moves in conjunction with the insurance sector,” Bates posited. But it’s thought that some hedge funds are testing strategies out to mine news and social media datasets for other types of correlations.
Crazy, right? Well, irrational on one level, perhaps, but those trading algos are big (bad) business: remember the guy who was accused of stealing some algo code from Goldman Sachs? Eight year stretch [via BoingBoing].