Monthly Archives: February 2012

GSoC Project #2 for 2012

In my prior post, I discussed the origins of the first GSoC project I posted this year.

The second GSoC project I’ve proposed is around the writing and code of Attilio Meucci, an adjunct professor at Baruch College – CUNY and an excellent speaker (I saw him at the University of Chicago when he spoke with Bob Litterman, and again at UIC’s Quant Fridays). He is also the chief risk officer at Kepos Capital LP.

He is also a thought leader in advanced risk and portfolio management. His innovations include Entropy Pooling (technique for fully flexible portfolio construction), Factors on Demand (on-the-fly factor model for optimal hedging), Effective Number of Bets (entropy-eigenvalue statistic for diversification management), Fully Flexible Probabilities (technique for on-the-fly stress-test and estimation without re-pricing), and Copula-Marginal Algorithm (algorithm to generate panic copulas).

Attillio is 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. Some of that code requires Matlab’s additional Optimization Toolkit. I’d like us to, during the course of the summer, convert some subset of his Matlab code to R to make it more widely assessible.

Beyond the initial conversion, we will functionalize key aspects of that code and consider including functions in PerformanceAnalytics, PortfolioAnalytics, or developing a package around one or more of the concepts described above, starting with the Effective Number of Bets.

Take a look at the project idea, where I’ve listed a couple of his papers that have links to the original Matlab code. If you’re a student who is interested and think you’re qualified (or even just have questions), please drop me a line.


A Heartfelt Thank You and the Resulting GSoC Project

PerformanceAnalytics has long enjoyed contributions from users who would like to see specific functionality included.

Diethelm Wuertz at ETHZ, who is the author and sponsor of all the various R/Metrics packages is one of those contributors. I first met Diethelm when he hosted a conference on high-frequency data in the early 1990’s (where we fretted about managing terabyte-sized databases), but it was his various R/Metrics packages that finally convinced me to use R. He was also keynote at our first R/Finance conference, where he demonstrated his talents in financial data visualization.

When I finally was able to attend his excellent conference in Meielisalp, he very generously contributed a very large set of functions that he had been working on from the second edition of Bacon (2008).

It pains me that it has taken so long to thank him publicly for that contribution. It only makes it worse that so much of that contribution has only slowly leaked into PerformanceAnalytics over time. Of the more than 100 functions he contributed, more than 50 have been incorporated, integrated with, or overlap with existing functions.

But there is still a fair amount of work to do. I’ve recently been focused on some of the downside metrics, things like average drawdowns. Some of the upside corollaries to downside statistics are interesting as well – measures such as upside potential, upside variance, and upside risk.

To help move this effort along, I proposed a Google Summer of Code project for 2012. Students, let me know if you are interested or even if you have any questions.

Diethelm’s original contributions can be found on r-forge in svn.

Again, many thanks to Diethelm!