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Topology of Foreign Exchange Markets using Hierarchical Structure Methods

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

This paper uses two 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 1996-2001. 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 guide to determining the underlying economic or regional causal relationships for individual currencies and will prove useful to understanding the dynamics of exchange rate price determination as part of a complex network.

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File URL: http://arxiv.org/pdf/physics/0608084
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Paper provided by arXiv.org in its series Papers with number physics/0608084.

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Date of creation: Aug 2006
Date of revision: Nov 2006
Handle: RePEc:arx:papers:physics/0608084
Contact details of provider: Web page: http://arxiv.org/

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  1. Rosario N. Mantegna, 1998. "Hierarchical Structure in Financial Markets," Papers cond-mat/9802256, arXiv.org.
  2. N. Vandewalle & F. Brisbois & X. Tordoir, 2001. "Non-random topology of stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 372-374.
  3. N. T. Laopodis, 2003. "Stochastic behaviour of Deutsche mark exchange rates within EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(9), pages 665-676.
  4. 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.
  5. Jeffrey A. Frankel & Andrew K. Rose, 1996. "Currency crashes in emerging markets: an empirical treatment," International Finance Discussion Papers 534, Board of Governors of the Federal Reserve System (U.S.).
  6. G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
  7. Hagen, Jurgen von & Fratianni, Michele, 1990. "German dominance in the EMS: evidence from interest rates," Journal of International Money and Finance, Elsevier, vol. 9(4), pages 358-375, December.
  8. Tanya Araujo & Francisco Louca, 2007. "The geometry of crashes. A measure of the dynamics of stock market crises," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 63-74.
  9. 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.
  10. 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.
  11. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 00/48, International Monetary Fund.
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