R/Finance 2010 … and unicorns

April 23, 2010

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

At the Information Management blogs, Steve Miller has posted a great roundup of last weekend’s R/Finance 2010 conference in Chicago. Here’s Steve’s overall take:

This year’s conference was even better than the 2009 inaugural, the in-excess-of-200 participants consumed by more than 20 consecutive high-powered presentations over the fast-paced day and a half. And while I’m a quantitative finance welterweight at best, there was plenty to pique my interest, including the latest developments to scale R for size and performance.

Check of the rest of Steve’s post for a great review of the other talks at the conference.

As Steve mentions, analysis of large data sets was a big focus of the conference with at least six presentations on the topic, including my own. I talked about a research project we’ve been working on at REvolution for a while, to make data processing and statistical analysis techniques for huge data sets available in REvolution R, breaking the bottlenecks of single-CPU processing, slow disk I/O processing, and being limited to RAM on just one machine. I deviated from the pre-advertised title, and the title in the slides, "A Herd of Unicorns" (download as PDF), may require a little explanation out of context. The "unicorn" here is something powerful and (at least today) mythical: the combination of analytic algorithms for really large data sets, and a flexible programming environment that enables modern statistical analysis: exploration, data manipulation, visualization, model evaluation. In other words, the R environment. And if you had the freedom to do large-scale data analysis in R, while making the use of the power of multiple machine in a cluster or in the cloud then that would be, well, a herd of unicorns. We’re working hard to make that fantasy a reality, soon. 

Information Management: R/Finance 2010: Applied Finance with R

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