Monthly Archives: January 2013

Visually Comparing Return Distributions

Here is a spot of code to create a series of small multiples for comparing return distributions. You may have spotted this in a presentation I posted about earlier, but I’ve been using it here and there and am finally satisfied that it is a generally useful view, so I functionalized it.

page.Distributions(edhec[,c("Convertible Arbitrage", "Equity Market Neutral","Fixed Income Arbitrage", "Event Driven", "CTA Global", "Global Macro", "Long/Short Equity")])

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R/Finance 2013 Call for Papers

It’s that time of year again – we’ve just posted our Call for Papers for the R/Finance 2013 conference, which focuses on applied finance using R. This is our fifth annual conference, again organized by a group of R package authors and community contributors and hosted by the International Center for Futures and Derivatives (ICFD) at the University of Illinois at Chicago.

The conference will be held this spring in Chicago, IL, on Friday May 17 and Saturday May 18, 2013.

I’m particularly excited about our lineup of speakers this year, which we’ve just finalized:

Sanjiv Das, who is a Professor of Finance and the Chair of the Finance Department at Santa Clara University’s Leavey School of Business. He is also the author of Derivatives: Principles and Practice, and he’s a senior editor of The Journal of Investment Management and co-editor of The Journal of Derivatives. You’ll find R spread through most of his work and his blog.

Attilio Meucci is the Chief Risk Officer at Kepos Capital, L.P. and author of Risk and Asset Allocation. He is a thought leader in advanced risk and portfolio management, and somewhat rare in the world of financial research in that he regularly posts code along with his working papers – a characteristic that I deeply appreciate. Unfortunately for me and the broader finance community for R, he prefers to code in Matlab. All of Meucci’s original MATLAB source is available on, but a recent Google Summer of Code project was dedicated to translating some of it to R.

Ryan Sheftel is a Managing Director for Electronic Market Making at Credit Suisse and has been introducing more and more automation for their Treasury bond execution services out to clients. He’s noted publicly that many of CS’ best traders spend a lot of time pounding away writing code – and, perhaps unusually for a senior manager at a large bank, spends time himself coding in R.

Ruey Tsay is a Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. R users may be interested in his new book, An Introduction to Analysis of Financial Data with R, or may already own an edition of Analysis of Financial Time Series, a core book that is well applied in his course on time series analysis at U of C. Also look for companion packages on CRAN.

Hopefully that will whet your appetite enough for you to make plans to attend.

But perhaps you should consider speaking. We’re looking for speakers who focus significantly on the application of R (and packages in R) in various applications to finance. We strongly encourage speakers provide working R code to accompany the presentation/paper, as our audience enjoys being able to take concrete ideas and apply them to their own problems after the conference.

Ideally, data sets would also be made public for the purposes of reproducibility (though we realize this may be limited due to contracts with data vendors). We tend to give preference to presenters who have released R packages.

As in previous years, we will keep all presentations in one track in a large presentation hall with dual projections screens and a stage. This allows all of our conference participants to see all presentations. Given that we have had well over 200 attendees in prior years and a mix of academics and practitioners, you should plan for this type of large and varied audience.

So, unlike an academic conference where you may be presenting your work to 10-15 people who are highly knowledgeable in your field of expertise, you will be presenting to an audience with more varied skills and interests: think TED talk and not detailed exposition of your theory to experts.

Presentations that have been best received in the past have clearly communicated the motivation for the work, and how it could be applied in practice. Presentation that have been less well received have sought to go through the detailed math behind the theories, or have an unclear link to R.

Hopefully that will give you a sense of what we’re looking for, assuming you haven’t attended before. This has been a conference I’ve really enjoyed in the past, and I’m sure this year will be no exception. Much of that comes from hanging out with the attendees – and I hope to see you there, too.