2009/05/29 by Daniel J. Fenn, Mason A. Porter, Fenn, Daniel J. +11
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Data Analysis #FOS: Economics and business #FOS: Physical sciences #Nonlinear Dynamics and Pattern Formation #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an) #Trading and Market Microstructure (q-fin.TR)
paper · pdf · doi:10.48550/arxiv.0905.4912
openalex publication_date 2009/05/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
We use techniques from network science to study correlations in the foreign exchange (FX) market over 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 time dynamics of this role. 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.