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Topology of foreign exchange markets using hierarchical structure methods

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Author Info

  • Naylor, Michael J.
  • Rose, Lawrence C.
  • Moyle, Brendan J.

Abstract

This paper uses two physics derived hierarchical techniques, a minimal spanning tree and an ultrametric hierarchical tree, to extract a topological influence map for major currencies from the ultrametric distance matrix for 1995–2001. We find that these two techniques generate a defined and robust scale free network with meaningful taxonomy. The topology is shown to be robust with respect to method, to time horizon and is stable during market crises. This topology, appropriately used, gives a useful guide to determining the underlying economic or regional causal relationships for individual currencies and to understanding the dynamics of exchange rate price determination as part of a complex network.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 382 (2007)
Issue (Month): 1 ()
Pages: 199-208

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Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:199-208

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Minimal spanning tree; Ultrametric hierarchical tree; Taxonomy; Econophysics; Financial markets;

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References

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  1. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 00/48, International Monetary Fund.
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  9. Tanya Ara\'{u}jo & Francisco Lou\c{c}\~{a}, 2005. "The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises," Papers physics/0506137, arXiv.org, revised Jul 2005.
  10. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
  11. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1998. "Noise dressing of financial correlation matrices," Science & Finance (CFM) working paper archive 500051, Science & Finance, Capital Fund Management.
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Citations

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Cited by:
  1. Leonidas Sandoval Junior, 2011. "Pruning a Minimum Spanning Tree," Papers 1109.0642, arXiv.org.
  2. Matesanz, David & Ortega, Guillermo J., 2008. "Network analysis of exchange data: Interdependence drives crisis contagion," MPRA Paper 7720, University Library of Munich, Germany.
  3. Oya, Shunsuke & Aihara, Kazuyuki & Hirata, Yoshito, 2014. "An absolute measure for a key currency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 15-23.
  4. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
  5. Carlos León & Ron J. Berndsen, 2013. "Modular scale-free architecture of Colombian financial networks: Evidence and challenges with financial stability in view," BORRADORES DE ECONOMIA 011104, BANCO DE LA REPÚBLICA.
  6. 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, vol. 4(1), pages 55-72, June.
  7. Sandoval, Leonidas, 2012. "Pruning a minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2678-2711.
  8. Aoki, Masanao & Hawkins, Raymond, 2009. "Macroeconomic Relaxation: Adjustment Processes of Hierarchical Economic Structures," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(17), pages 1-21.
  9. Wang, Gang-Jin & Xie, Chi & Han, Feng & Sun, Bo, 2012. "Similarity measure and topology evolution of foreign exchange markets using dynamic time warping method: Evidence from minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4136-4146.
  10. Janusz Mi\'skiewicz, 2012. "Network analysis of correlation strength between the most developed countries," Papers 1211.3599, arXiv.org.
  11. Rea, Alethea & Rea, William, 2014. "Visualization of a stock market correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 109-123.
  12. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
  13. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
  14. Materassi, Donatello & Innocenti, Giacomo, 2009. "Unveiling the connectivity structure of financial networks via high-frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3866-3878.
  15. Khaldoun Khashanah & Linyan Miao, 2011. "Dynamic structure of the US financial systems," Studies in Economics and Finance, Emerald Group Publishing, vol. 28(4), pages 321-339, October.
  16. Donatello W. Materassi & Giacomo W. Innocenti, 2008. "Topological identification in networks of dynamical systems," Papers 0804.2441, arXiv.org, revised Jul 2008.

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