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Scale free effects in world currency exchange network

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  • A. Z. Gorski
  • S. Drozdz
  • J. Kwapien

Abstract

A large collection of daily time series for 60 world currencies' exchange rates is considered. The correlation matrices are calculated and the corresponding Minimal Spanning Tree (MST) graphs are constructed for each of those currencies used as reference for the remaining ones. It is shown that multiplicity of the MST graphs' nodes to a good approximation develops a power like, scale free distribution with the scaling exponent similar as for several other complex systems studied so far. Furthermore, quantitative arguments in favor of the hierarchical organization of the world currency exchange network are provided by relating the structure of the above MST graphs and their scaling exponents to those that are derived from an exactly solvable hierarchical network model. A special status of the USD during the period considered can be attributed to some departures of the MST features, when this currency (or some other tied to it) is used as reference, from characteristics typical to such a hierarchical clustering of nodes towards those that correspond to the random graphs. Even though in general the basic structure of the MST is robust with respect to changing the reference currency some trace of a systematic transition from somewhat dispersed -- like the USD case -- towards more compact MST topology can be observed when correlations increase.

Suggested Citation

  • A. Z. Gorski & S. Drozdz & J. Kwapien, 2008. "Scale free effects in world currency exchange network," Papers 0810.1215, arXiv.org.
    • Handle: RePEc:arx:papers:0810.1215
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    File URL: http://arxiv.org/pdf/0810.1215
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    Cited by:

    1. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    2. Jarosław Kwapień & Sylwia Gworek & Stanisław Drożdż & Andrzej Górski, 2009. "Analysis of a network structure of the foreign currency exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(1), pages 55-72, June.
    3. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    4. Nguyen, Q. & Nguyen, N.K. K. & Nguyen, L.H. N., 2019. "Dynamic topology and allometric scaling behavior on the Vietnamese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 235-243.
    5. Nguyen, Q. & Nguyen, N.K.K., 2019. "Composition of the first principal component of a stock index — A comparison between SP500 and VNIndex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    6. Jaroslaw Kwapien & Sylwia Gworek & Stanislaw Drozdz & Andrzej Gorski, 2009. "Analysis of a network structure of the foreign currency exchange market," Papers 0906.0480, arXiv.org.

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