MIT Startup Flyberry Capital Emerges with Big-Data Hedge Fund

Hedge funds in general haven’t performed well in recent years. Investors are wary of new financial strategies. And any firm can say it has some black-box system that can predict the market. Barakat, an MIT Sloan School grad and entrepreneur, shuns the black-box approach, saying Flyberry only uses trading strategies that it understands. “At the end of the day, it’s all about your returns and how successful you are,” he says. “People don’t have to take our word on this. They can see our trade results.”

So far, things are looking good. Flyberry has advanced to the finals of a hedge fund competition this summer sponsored by Lion’s Path Capital. (The other finalist is SLCM Capital, a New York startup.) In doing so, Flyberry is likely to secure $1 million in trading funds, and has shown gross returns of 6 percent over the month-long competition. (The company has been doing real trades since April but, for legal reasons, is unable to broadly disclose its trade results. “Believe me, we would like to,” says Barakat.) The winner of the final round could receive $25 million to work with down the road, at which point Lion’s Path would take an equity stake.

Flyberry currently has eight full-time employees and has raised about $500,000 in angel funding. The startup has some themes in common with other tech companies like Recorded Future (Web analytics and predictions), Fina Technologies (data-based trading algorithms), Quant5 (analytics for marketing), Lexalytics (text analysis), and Bluefin Labs (social media around TV).

So how big could Flyberry get? Chang is pretty bullish on the opportunity, not surprisingly. He expects the company will have more than $100 million under management within about a year, and over $1 billion within five years. Those are big numbers. He also wants to establish a big brand presence in Asia.

To get there, of course, the Flyberry team will have to adjust its trading models if they’re not working, and continue to develop new models to stay ahead of the curve. And it will probably need to find new revenue streams. But that’s where the firm’s multiple-model approach should pay off, says Barakat.

Still, he admits, “nobody knows what’s going to happen in the future…but we like our odds.”

Author: Gregory T. Huang

Greg is a veteran journalist who has covered a wide range of science, technology, and business. As former editor in chief, he overaw daily news, features, and events across Xconomy's national network. Before joining Xconomy, he was a features editor at New Scientist magazine, where he edited and wrote articles on physics, technology, and neuroscience. Previously he was senior writer at Technology Review, where he reported on emerging technologies, R&D, and advances in computing, robotics, and applied physics. His writing has also appeared in Wired, Nature, and The Atlantic Monthly’s website. He was named a New York Times professional fellow in 2003. Greg is the co-author of Guanxi (Simon & Schuster, 2006), about Microsoft in China and the global competition for talent and technology. Before becoming a journalist, he did research at MIT’s Artificial Intelligence Lab. He has published 20 papers in scientific journals and conferences and spoken on innovation at Adobe, Amazon, eBay, Google, HP, Microsoft, Yahoo, and other organizations. He has a Master’s and Ph.D. in electrical engineering and computer science from MIT, and a B.S. in electrical engineering from the University of Illinois, Urbana-Champaign.