Universities Put “Blue Gene” Machines in Cloud, To Help Hedge Funds Trade
June 7, 2010
Two hedge funds – a start-up and another based on Long Island – are set to tap high-performance computing systems owned by Stony Brook University through a “cloud” of networks that connect firms to available processing capacity at the school.
Separately, FINA Technologies, a Cambridge, Mass.-based hedge fund technology supplier spun out of Gene Network Sciences, is renting cycles on Rensselaer Polytechnic Institute’s IBM Blue Gene supercomputer located in North Greenbush, N.Y. FINA will use one of academia’s largest supercomputing centers to redeploy software originally used to analyze gene sequences for optimal drug therapies to divine money-making opportunities in the capital markets.
The start-up fund working with Stony Brook “will use a mixture of ordinary and high-performance computing to design trading strategies,’’ according to James Glimm, distinguished professor and chair of the department of applied mathematics and statistics at Stony Brook.
This may involve using cycles on New York Blue, a massively parallel IBM Blue Gene machine housed at Brookhaven National Laboratory, located in Upton, N.Y., and owned by Stony Brook. Stony Brook has created what it calls “a university research cloud,” in which hedge funds can contract to use supercomputing power from Blue and other of the school’s processing resources.
Another fund, which Glimm would only describe as Long Island-based, is working with Stony Brook to develop a trading system that aims to spot price and risk anomalies in the market – gaps where money can be made – by combing massive amounts of market data. The work involves “developing software to power a trading system, drawn in part from high-performance computing, meant to solve a mixture of large and small data analysis problems,” he said.
Because of non-disclosure agreements, Glimm would not provide further details, except to say he and the university “are working with other hedge funds on a variety of software projects.”
But he said the work will draw from a big baseline data crunch, powered by the school’s supercomputer.
“New York Blue will be used for a large calculation to provide what you might call a ‘Bayesian prior’ of the stock market,” Glimm said. “It gives you sort of a universal view of everything. This is where you need huge amounts of data and processing.”
A Bayesian prior is basically aimed at estimating the likelihood of an event – a prediction, essentially – based on analysis of historical and incoming, new data.
“When you get to the trading part after analyzing the data to determine ‘that’s my world view,’ what you do about it tomorrow using these findings is probably a smaller problem, which wouldn’t go on Blue,” he said.
Stony Brook is one of several intellectual ground zeros for quantitative finance. The Long Island institution is home to Nobel prize-winners such as C.N. Yang (Physics, 1957) and Robert J. Aumann (Economics, 2005); famous mathematicians such as Glimm and Dennis Sullivan -- and alma mater of arguably the most successful hedge fund manager in history: Renaissance Technologies’ founder James Simons. One of Simons’ several notable achievements: Renaissance’s Medallion fund’s 45-percent average annual returns since 1988.
