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Analysis of Linkage Effects among Currency Networks Using REER Data

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  • Haishu Qiao
  • Ying Li
  • Yue Xia

Abstract

We modeled the currency networks through the use of REER (real effective exchange rate) instead of a bilateral exchange rate in order to overcome the confusion in selecting base currencies. Based on the MST (minimum spanning tree) approach and the rolling-window method, we constructed time-varying and correlation-based networks with which we investigate the linkage effects among different currencies. In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. The study demonstrated that obvious linkage effects existed among currency networks and the euro (EUR) was confirmed as the predominant world currency. Additionally, we used the rolling-window method to investigate the stability of linkage effects, doing so by calculating the mean correlations and mean distances as well as the normalized tree length and degrees of those currencies. The results showed that financial crises during the study period had a great effect on the currency network’s topology structure and led to more clustered currency networks. Our results suggested that it is more appropriate to estimate the linkage effects among currency networks through the use of REER data.

Suggested Citation

  • Haishu Qiao & Ying Li & Yue Xia, 2015. "Analysis of Linkage Effects among Currency Networks Using REER Data," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-9, May.
    • Handle: RePEc:hin:jnddns:641907
    DOI: 10.1155/2015/641907
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    Cited by:

    1. Wang, Gang-Jin & Wan, Li & Feng, Yusen & Xie, Chi & Uddin, Gazi Salah & Zhu, You, 2023. "Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Samitas, Aristeidis & Kampouris, Elias & Kenourgios, Dimitris, 2020. "Machine learning as an early warning system to predict financial crisis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).

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