Detecting a currency's dominance or dependence using foreign exchange network trees

Mark McDonald, Omer Suleman, Stacy Williams, Sam Howison, Neil F Johnson

Research output: Contribution to journalArticle

52 Citations (Scopus)

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.

Original languageEnglish (US)
Article number046106
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume72
Issue number4
DOIs
StatePublished - Oct 2005
Externally publishedYes

Fingerprint

Tree Networks
Currency
Minimum Spanning Tree
network analysis
Global Dynamics
Interdependencies
Exchange rate
stochastic processes
Network Analysis
Tie
Period of time
correlation coefficients
Correlation coefficient
Stochastic Processes
Dependent
Market

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Mathematical Physics

Cite this

Detecting a currency's dominance or dependence using foreign exchange network trees. / McDonald, Mark; Suleman, Omer; Williams, Stacy; Howison, Sam; Johnson, Neil F.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 72, No. 4, 046106, 10.2005.

Research output: Contribution to journalArticle

McDonald, Mark ; Suleman, Omer ; Williams, Stacy ; Howison, Sam ; Johnson, Neil F. / Detecting a currency's dominance or dependence using foreign exchange network trees. In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 2005 ; Vol. 72, No. 4.
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