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Evolutionary Topology Of A Currency Network In Asia

Author

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  • XIAOBING FENG

    (College of Finance, Shanghai Institute of Foreign Trade, Shanghai 200240, China;
    Complex Networks and Control Lab, Department of Automations, Shanghai Jiaotong University, 200240, China)

  • XIAOFAN WANG

    (Complex Networks and Control Lab, Department of Automations, Shanghai Jiaotong University, 200240, China)

Abstract

Although recently there are extensive research on currency network using minimum spanning trees approach, the knowledge about the actual evolution of a currency web in Asia is still limited. In the paper, we study the structural evolution of an Asian network using daily exchange rate data. It was found that the correlation between Asian currencies and US Dollar, the previous regional key currency has become weaker and the intra-Asia interactions have increased. This becomes more salient after the exchange rate reform of China. Different from the previous studies, we further reveal that it is the trade volume, national wealth gap and countries growth cycle that has contributed to the evolutionary topology of the minimum spanning tree. These findings provide a valuable platform for theoretical modeling and further analysis.

Suggested Citation

  • Xiaobing Feng & Xiaofan Wang, 2010. "Evolutionary Topology Of A Currency Network In Asia," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 471-480.
    • Handle: RePEc:wsi:ijmpcx:v:21:y:2010:i:04:n:s0129183110015269
    DOI: 10.1142/S0129183110015269
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    Citations

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    Cited by:

    1. 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.
    2. Kantar, Ersin & Aslan, Alper & Deviren, Bayram & Keskin, Mustafa, 2016. "Hierarchical structure of the countries based on electricity consumption and economic growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 1-10.
    3. 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.

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