Computational Finance - University of Washington

R Computing Focus

The CompFin Program at the University of Washington makes extensive use of the open source R language and computing environment in its instructional program and in research. We believe that R is an ideal tool for: (a) financial data modeling and analysis using existing R finance capabilities, (b) rapid development and deployment of new quantitative finance methodology, (c) teaching of standard and cutting-edge quantitative finance methodology.

R Packages for Quantitative Finance

There are hundreds of R packages that support state of the art modeling and analysis of financial data. See for example the R empirical finance packages at the following Comprehensive R Archive Network (CRAN) site link:

http://cran.fhcrc.org/web/views/Finance.html

See also packages for topics such as Econometrics, Time Series, Optimization, Machine Learning and High Performance Computing at

http://cran.fhcrc.org/web/views

Annual R-Finance Conference

The third annual R-Finance conference was held on April 28-29, 2011, with four keynote sessions, 17 presentations and 12 lightening talks. This year’s conference had over 200 attendees, with 70-75% of these being from the finance industry. CompFin program Director Doug Martin, Co-Director Eric Zivot, and Affiliate Instructor Guy Yollin all made presentations at the 2011 conference. For details see the R-Finance web site (http://www.rinfinance.com/), where slides for this year’s and prior years’ presentations may be found.

Rapid Growth in the Use of R

Since its introduction in the late 1990's the use of R has grown at a startling rate and R and has emerged as the de facto open source standard for statistical computing, data analysis, and graphics. See for example

http://sites.google.com/site/r4statistics/popularity

Background on R

R is based on the S language developed by John Chambers at AT&T Bell Labs, with extensive contributions from Rick Becker and a number of Bell Labs colleagues focused on challenging data analysis problems and use of new statistical methodologies. Dr. Chambers received the ACM Software System award of 1998:

www.acm.org/announcements/ss99.html

The support of the Statistical Research group that was located in the Bell Labs Mathematics Research Center located in Murray Hill, NJ, combined with the overall research environment at Bell Labs prior to the AT&T divestiture, provided a unique and ideal setting for the development and rapid evolution of S.

Much of the initial growth in the development and use of R can be attributed to the success of the S-PLUS product which was a commercial implementation of the S language by Statistical Sciences, Inc. (a company founded by CompFin Program Director Doug Martin).

Robert Gentleman and Ross Ihaka received the 2010 American Statistical Association Statistical Computing and Graphics Award for their work in initiating the R Project for Statistical Computing:

http://stat-computing.org/awards/comp-graphics/winners.html

For a brief overview of R, it’s history, and an introduction to R programming, see "Introduction to R" by Guy Yollin

Further information and to download R, visit www.r-project.org

Other Quantitative Finance Computing Systems

From time to time other commercial quantitative finance computing systems will be used in support of the CompFin program, including portfolio construction and risk management systems. Current examples include the following:

Computational Finance and Risk Management, University of Washington, Guggenheim Hall #414, Box 352420, Seattle, WA 98195-2420 USA
Email 'compfin' (at uw.edu) Phone 206-543-5493 Fax 206-685-1440