"Dynamical Clustering of Exchange Rates"

This paper is another one of those papers that my collaborators and I submitted to a journal a long time ago (in this case, in spring 2009) that has only now appeared in final form. Hence, although it's a new paper in some sense of the word, it certainly doesn't feel new. Here are some details:

Title: Dynamical Clustering of Exchange Rates

Authors: Daniel J. Fenn, Mason A. Porter, Peter J. Mucha, Mark McDonald, Stacy Williams, Neil F. Johnson, and Nick S. Jones

Abstract: We use techniques from network science to study correlations in the foreign exchange (FX) market during the period 1991–2008. We consider an FX market network in which each node represents an exchange rate and each weighted edge represents a time-dependent correlation between the rates. To provide insights into the clustering of the exchange-rate time series, we investigate dynamic communities in the network. We show that there is a relationship between an exchange rate’s functional role within the market and its position within its community and use a node-centric community analysis to track the temporal dynamics of such roles. This reveals which exchange rates dominate the market at particular times and also identifies exchange rates that experienced significant changes in market role. We also use the community dynamics to uncover major structural changes that occurred in the FX market. Our techniques are general and will be similarly useful for investigating correlations in other markets.



Note: I know I have brought this one up before in my blog and it did appear online after dealing with page proofs a couple of months ago, but it now has page numbers, etc.