Below is a chart of the top 20 offensive players based on FanGraphs WAR for the 2011 season. The various features and their corresponding metric are clear in the image. I’ve also included the leader and last place for each … Continue reading →

Bill Bolstad wrote a reply to my review of his book Understanding computational Bayesian statistics last week and here it is, unedited except for the first paragraph where he thanks me for the opportunity to respond, “so readers will see that the book has some good features beyond having a “nice cover”.” (!) I simply processed

There is a call for postdoctoral positions supported by the Paris Mathematical Sciences Foundation. The deadline is December 13 and the on-line application is available. If you are interested in working with me on Bayesian statistics (model choice, time series model) or computational methods (SMC, MCMC, ABC, &c.) thru this call, please contact me at

The Minimum Investment and Number of Assets Portfolio Cardinality Constraints are practical constraints that are not easily incorporated in the standard mean-variance optimization framework. To help us impose these real life constraints, I will introduce extra binary variables and will use mixed binary linear and quadratic programming solvers. Let’s continue with our discussion from Introduction

Pierre Jacob and Robin Ryder (from Paris-Dauphine, CREST, and Statisfaction) have just arXived (and submitted to the Annals of Applied Probability) a neat result on the Wang-Landau algorithm. (This algorithm, which modifies the target in a sort of reweighted partioned sampling to achieve faster convergence, has always been perplexing to me.) They show that some

The 130/30 funds were getting lots of attention a few years ago. The 130/30 fund is a long/short portfolio that for each $100 dollars invested allocates $130 dollars to longs and $30 dollars to shorts. From portfolio construction perspective this simple idea is no so simple to implement. Let’s continue with our discussion from Introduction

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