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Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis

Author

Listed:
  • Daniel J. Fenn
  • Mason A. Porter
  • Mark McDonald
  • Stacy Williams
  • Neil F. Johnson
  • Nick S. Jones

Abstract

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using dynamical community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.

Suggested Citation

  • Daniel J. Fenn & Mason A. Porter & Mark McDonald & Stacy Williams & Neil F. Johnson & Nick S. Jones, 2008. "Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis," Papers 0811.3988, arXiv.org, revised Jul 2009.
    • Handle: RePEc:arx:papers:0811.3988
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    File URL: http://arxiv.org/pdf/0811.3988
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    Cited by:

    1. Marya Bazzi & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2014. "Community detection in temporal multilayer networks, with an application to correlation networks," Papers 1501.00040, arXiv.org, revised Dec 2017.
    2. Carlo Piccardi, 2011. "Finding and Testing Network Communities by Lumped Markov Chains," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
    3. Jaroonchokanan, Nawee & Termsaithong, Teerasit & Suwanna, Sujin, 2022. "Dynamics of hierarchical clustering in stocks market during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Loretti I. Dobrescu & Mihaela Neamtu & Gabriela Mircea, 2016. "Asset Price Dynamics in a Chartist-Fundamentalist Model with Time Delays: A Bifurcation Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-15, February.
    5. Xin Yang & Shigang Wen & Zhifeng Liu & Cai Li & Chuangxia Huang, 2019. "Dynamic Properties of Foreign Exchange Complex Network," Mathematics, MDPI, vol. 7(9), pages 1-19, September.

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