Numerai, a New Hedge Fund That Uses Artificial Intelligence and Bitcoins

A startup company named Numerai is exploiting AI in the best way possible. Richard Craib, the founder of the company, runs the company without much effort, all because of AI. Numerai is a new kind of hedge fund created by a chain of data scientists and is based in San Francisco.

It is interesting to note that Carib and his team came up with a way of coding the fund’s trading data, so the data scientists are denied access to all the trading information. In doing so the team has used a similar method like homomorphic encryption, the company ensures that the details like the company’s proprietary trades are not revealed to the data scientists.The data is encrypted in such a way that the data scientists can organise the data accordingly so as to build machine learning models that analyses the data and thereon produces a theory which allows better ways of trading.

The company maintains the anonymity of the data scientist. Carib explained, “Anyone can submit predictions back to us.” “If they work, we pay them in bitcoin.”

Numerai’s funds have been trading stocks for a year now. The company has got big investors like Renaissance Technologies. The company has completed its first venture funding led by the New York venture capital firm Union Square Ventures. Union Square company has invested $3 million in the round, with an additional $3 million coming from others.

The idea had striked Carib when he was working for a financial firm in South Africa. He shared, “That’s when I started looking into these new ways of encrypting data—looking for a way of sharing the data with him without him being able to steal it and start his hedge fund.”

Numerai so as to come up with better solutions is employing a stacking or ensembling. It is a statistics and machine learning technique which combine the best of myriad algorithms to create better results.

Employing such a method ensures the privacy of the customers of the service and simultaneously achieve accurate results.



Shobith MAKAM Written by: