Last week I attended the R/Finance conference held in Chicago. About 300 developers, academics, and practitioners gathered at the two-day conference to discuss the latest applications of the R open-source programming language to finance. I’ve mostly coded in Matlab, but the growing popularity of R and the number of people developing leading edge statistical packages in R have made it impossible to ignore.

In case you’ve been hiding under a rock, here is a 90 second video that gives an introduction to R. The R language was originally developed by statisticians and has been perceived as being more suited for small data problems. (Machine learning people, of course, tend to prefer Matlab.) However, I think this view is increasingly obsolete. A number of talks at the conference focused on using R in high performance applications (by using calls to C++, for example) or with very large datasets (by using Hadoop at the backend).

For me, the most interesting presentations were those on applying R to market forecasting over the business cycle. The scarcest resource in developing trading strategies is the researcher’s time. If R can increase your productivity given its large library of packages, it’s well worth looking into.

The conference presentations have just been made available online. You can find them at the conference website.