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Topology of foreign exchange markets using hierarchical structure methods

Author

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  • 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.

Suggested Citation

  • Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
    • Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:199-208
    DOI: 10.1016/j.physa.2007.02.019
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    1. 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.
    2. 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.
    3. Jeffrey A. Frankel & Giampaolo Galli & Alberto Giovannini, 1996. "Introduction to "The Microstructure of Foreign Exchange Markets"," NBER Chapters, in: The Microstructure of Foreign Exchange Markets, pages 1-18, National Bureau of Economic Research, Inc.
    4. Mr. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 2000/048, International Monetary Fund.
    5. 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.
    6. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    7. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    8. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    9. Michele Fratianni & Juergen Hagen, 1990. "German dominance in the EMS," Open Economies Review, Springer, vol. 1(1), pages 67-87, February.
    10. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
    11. Giovanni Bonanno & Nicolas Vandewalle & Rosario N. Mantegna, 2000. "Taxonomy of Stock Market Indices," Papers cond-mat/0001268, arXiv.org, revised Aug 2000.
    12. Neil F. Johnson & Mark McDonald & Omer Suleman & Stacy Williams & Sam Howison, 2005. "What shakes the FX tree? Understanding currency dominance, dependence and dynamics," Papers physics/0503014, arXiv.org.
    13. 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.
    14. Tanya Ara'ujo & Francisco Louc{c}~a, 2005. "The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises," Papers physics/0506137, arXiv.org, revised Jul 2005.
    15. 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.
    16. Lillo, Fabrizio & Mantegna, Rosario N, 2004. "Dynamics of a financial market index after a crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 125-134.
    17. 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.
    18. Jeffrey A. Frankel & Giampaolo Galli & Alberto Giovannini, 1996. "The Microstructure of Foreign Exchange Markets," NBER Books, National Bureau of Economic Research, Inc, number fran96-1, July.
    19. N. Vandewalle & F. Brisbois & X. Tordoir, 2001. "Non-random topology of stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 372-374, March.
    Full references (including those not matched with items on IDEAS)

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