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Contagion among major world markets: a wavelet approach


  • Mikko Ranta


Purpose - The purpose of this paper is to examine contagion among the major world markets during the last 25 years and propose a new way to analyze contagion with wavelet methods. Design/methodology/approach - The analysis uses a novel way to study contagion using wavelet methods. The comparison is made between co-movements at different time scales. Co-movement methods of the discrete wavelet transform and the continuous wavelet transform are applied. Findings - Clear signs of contagion among the major markets are found. Short time scale co-movements increase during the major crisis while long time scale co-movements remain approximately at the same level. In addition, gradually increasing interdependence between markets is found. Research limitations/implications - Because of the chosen method, the approach is limited to large data sets. Practical implications - The research has practical implications to portfolio managers etc. who wish to have better view of the dynamics of the international equity markets. Originality/value - The research uses novel wavelet methods to analyze world equity markets. These methods allow the markets to be analyzed in the whole state space.

Suggested Citation

  • Mikko Ranta, 2013. "Contagion among major world markets: a wavelet approach," International Journal of Managerial Finance, Emerald Group Publishing, vol. 9(2), pages 133-149, March.
  • Handle: RePEc:eme:ijmfpp:v:9:y:2013:i:2:p:133-149

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    References listed on IDEAS

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    2. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2014. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis V.S. Wavelet Analysis," Working Papers 2014-577, Department of Research, Ipag Business School.
    3. Berger, Theo, 2015. "A wavelet based approach to measure and manage contagion at different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 338-350.
    4. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Kumar, Ronald Ravinesh & Mensi, Walid, 2017. "Interdependence and contagion among industry-level US credit markets: An application of wavelet and VMD based copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 310-324.
    5. Burzala, Milda Maria, 2016. "Contagion effects in selected European capital markets during the financial crisis of 2007–2009," Research in International Business and Finance, Elsevier, vol. 37(C), pages 556-571.
    6. Cipollini, Andrea & Cascio, Iolanda Lo & Muzzioli, Silvia, 2015. "Volatility co-movements: A time-scale decomposition analysis," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 34-44.
    7. Jozef BARUNÍK & Lukáš VÁCHA, 2013. "Contagion among Central and Eastern European Stock Markets during the Financial Crisis," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 443-453, November.
    8. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2015. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 575-611, December.
    9. da Silva, Marcus Fernandes & de Area Leão Pereira, Éder Johnson & da Silva Filho, Aloisio Machado & de Castro, Arleys Pereira Nunes & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2016. "Quantifying the contagion effect of the 2008 financial crisis between the G7 countries (by GDP nominal)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 1-8.
    10. Yang, Lu & Cai, Xiao Jing & Zhang, Huimin & Hamori, Shigeyuki, 2016. "Interdependence of foreign exchange markets: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 55(C), pages 6-14.
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