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Network analysis of exchange data: interdependence drives crisis contagion

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  • David Matesanz
  • Guillermo Ortega

Abstract

In this paper, we examine linear and nonlinear co-movements that appear in the real exchange rates of a group of 28 developed and developing countries. The matrix of Pearson correlation and Phase Synchronous coefficients have been used in order to construct a topology and hierarchy of countries by using the Minimum Spanning Tree (MST). In addition, the MST cost and global correlation coefficients have been calculated to observe the co-movements’ dynamics throughout the time sample. By comparing Pearson and Phase Synchronous information, a new methodology is emphasized; one that can uncover meaningful information pertaining to the contagion economic issue and, more generally, the debate surrounding interdependence and/or contagion in financial time series. Our results suggest some evidence of contagion in the Asian currency crises; however, this contagion is driven by previous and stable interdependence. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • David Matesanz & Guillermo Ortega, 2014. "Network analysis of exchange data: interdependence drives crisis contagion," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1835-1851, July.
    • Handle: RePEc:spr:qualqt:v:48:y:2014:i:4:p:1835-1851
    DOI: 10.1007/s11135-013-9855-z
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    2. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    3. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    4. Kireyev, A., 2019. "A Network Model of Multilateral Equilibrium Exchange Rates," Journal of the New Economic Association, New Economic Association, vol. 41(1), pages 12-33.
    5. Esmalifalak, Hamidreza, 2022. "Euclidean (dis)similarity in financial network analysis," Global Finance Journal, Elsevier, vol. 53(C).
    6. Mengdi Song, 2018. "Network Effects of Countries’ Exchange Rate Regime Choices: A Spatial Analysis," Open Economies Review, Springer, vol. 29(5), pages 1061-1093, November.
    7. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    8. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhai, Kaikai, 2021. "Multiscale and partial correlation networks analysis of risk connectedness in global equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    9. Xie Chi & Zhou Yingying & Wang Gangjin & Yan Xinguo, 2017. "Investigating the Disparities of China’s Insurance Market Based on Minimum Spanning Tree from the Viewpoint of Geography and Enterprise," Journal of Systems Science and Information, De Gruyter, vol. 5(3), pages 216-228, June.
    10. 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 1 & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    11. Xu, Helian & Cheng, Long, 2016. "The QAP weighted network analysis method and its application in international services trade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 91-101.
    12. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    13. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).

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    More about this item

    Keywords

    Crises; Exchange Rate; Hierarchical Tree;
    All these keywords.

    JEL classification:

    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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