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Modelling Profitabilities of Stock Indices Using Methods of Wavelet Analysis


  • Kravets Tatiana V.

    () (Kyiv National University named after T. Shevchenko)


The article considers specific features of European stock indices and conducts their comparative analysis. The goal of the study lies in localisation and description of crisis effects by time and scale in the dynamics of indices with the help of the wavelet transformation. This approach allows revelation of clusters of stock indices and study of their common and individual specific features. Combination of the wavelet-transformation, neural networks and SSA methods is used for forecasting dynamics of indices.

Suggested Citation

  • Kravets Tatiana V., 2013. "Modelling Profitabilities of Stock Indices Using Methods of Wavelet Analysis," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 7, pages 104-109.
  • Handle: RePEc:idp:bizinf:y:2013:i:7:p:104_109

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    References listed on IDEAS

    1. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    2. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists ," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    3. Enrico Capobianco, 2004. "Multiscale Analysis of Stock Index Return Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 23(3), pages 219-237, April.
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