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Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets

Author

Listed:
  • Jasmina Ðuraškovic

    (Institute of Economic Sciences, Belgrade, Serbia)

  • Slavica Manic

    (Faculty of Economics in Belgrade, University of Belgrade, Serbia)

  • Dejan Živkov

    (Novi Sad Business School, Serbia)

Abstract

This paper investigates volatility transmission and portfolio construction between the three Baltic stock indices at different time-horizons. Methodologies used for this study encompass parametric EGARCH model and the three non-parametric approaches – wavelet coherence, wavelet correlation and phase difference. Wavelet coherence indicated that risk integration between the Baltic stock markets is not so strong, while wavelet correlations confirmed this contention more precisely. Additional analysis showed that low wavelet correlations are also present between the Baltic indices and the German DAX index. These findings may suggest that the selected indices could be useful for the construction of risk-minimizing portfolios. In order to confirm (discard) this assumption, we constructed wavelet-based two-asset portfolios. The results provided evidence that hedging opportunities exist when the Baltic indices are combined between themselves, but also when they are coupled with the DAX index. This is particularly true for the longer time-horizons.

Suggested Citation

  • Jasmina Ðuraškovic & Slavica Manic & Dejan Živkov, 2019. "Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(2), pages 211-235, April.
  • Handle: RePEc:fau:fauart:v:69:y:2019:i:2:p:211-235
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    More about this item

    Keywords

    Baltic stock indices; volatility transmission; EGARCH model; wavelet coherence; wavelet correlation; phase difference;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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