Detecting a currency's dominance or dependence using foreign exchange network trees.
Phys Rev E Stat Nonlin Soft Matter Phys
; 72(4 Pt 2): 046106, 2005 Oct.
Article
em En
| MEDLINE
| ID: mdl-16383467
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.
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01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2005
Tipo de documento:
Article