Detecting a currency’s dominance or dependence using foreign exchange network trees
- 7 October 2005
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review E
- Vol. 72 (4), 046106
- https://doi.org/10.1103/physreve.72.046106
Abstract
In a system containing a large number of interacting stochastic processes, there will typically be many nonzero correlation coefficients. This makes it difficult to either visualize the system’s interdependencies, or identify its dominant elements. Such a situation arises in foreign exchange (FX), which is the world’s biggest market. Here we develop a network analysis of these correlations using minimum spanning trees (MSTs). We show that not only do the MSTs provide a meaningful representation of the global FX dynamics, but they also enable one to determine momentarily dominant and dependent currencies. We find that information about a country’s geographical ties emerges from the raw exchange-rate data. Most importantly from a trading perspective, we discuss how to infer which currencies are “in play” during a particular period of time.Keywords
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