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posted by janrinok on Sunday December 18 2016, @02:55PM   Printer-friendly

The latest issue of Wired has an interesting article about a 29 year old mathematician who is using crowd sourced machine learning to manage hedge funds.

Richard Craib is a 29-year-old South African who runs a hedge fund in San Francisco. Or rather, he doesn't run it. He leaves that to an artificially intelligent system built by several thousand data scientists whose names he doesn't know.

Under the banner of a startup called Numerai, Craib and his team have built technology that masks the fund's trading data before sharing it with a vast community of anonymous data scientists. Using a method similar to homomorphic encryption, this tech works to ensure that the scientists can't see the details of the company's proprietary trades, but also organizes the data so that these scientists can build machine learning models that analyze it and, in theory, learn better ways of trading financial securities.

"We give away all our data," says Craib, who studied mathematics at Cornell University in New York before going to work for an asset management firm in South Africa. "But we convert it into this abstract form where people can build machine learning models for the data without really knowing what they're doing."

He doesn't know these data scientists because he recruits them online and pays them for their trouble in a digital currency that can preserve anonymity. "Anyone can submit predictions back to us," he says. "If they work, we pay them in bitcoin."

So, to sum up: They aren't privy to his data. He isn't privy to them. And because they work from encrypted data, they can't use their machine learning models on other data—and neither can he. But Craib believes the blind can lead the blind to a better hedge fund.


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  • (Score: 2) by goodie on Sunday December 18 2016, @07:03PM

    by goodie (1877) on Sunday December 18 2016, @07:03PM (#442748) Journal

    This is somewhat like Kaggle competitions but for financial data?

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