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Netezza vs. the Cloud: Using R to Profile Distributed Computing Platforms with Applications in Backtesting FINRA's Limit Up/Down Rules


Michael Kane, Associate Research Scientist, Yale Center for Analytical Sciences
Casey King, Executive Director, Yale Center for Analytical Sciences

Yale researchers Michael Kane, PhD and Casey King, PhD considered the FINRA rules through the lens of historical data analysis. By looking at roughly 24 billion trades from 2008-2010, the researchers studied the efficacy of the FINRA rules, as featured in the August 15, 2011 issue of Barrons. A timely analysis of market data on this massive scale poses serious computational challenges. In this webinar, three techniques are compared to meet the challenge:1. Parallel computing in R, highlighted by the use of the iterators and foreach packages.2. Cloud computing using Amazon Web Services3. A joint solution using IBM Netezza analytic appliances integrated with Revolution R Enterprise, an enterprise-ready distribution of R from Revolution Analytics.While each technique effectively meets the challenge of this massively parallel problem, the Netezza and Revolution R Enterprise solution has proven to bring analysis time down from a matter of months, to a matter of hours. Join the webcast to learn how these Yale Researchers were able to innovate their models and extend their analysis using the integrated solution.