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Assessing Permanent and Transitory Volatility Spillover Effect from Oil to Stocks in Baltic and Visegrad Countries

Author

Listed:
  • Dejan Živkov

    (University of Novi Sad)

  • Marina Gajic-Glamoclija

    (University Business Academy in Novi Sad)

  • Jasmina Duraskovic

    (Project Management College)

  • Mirela Momcilovic

    (University of Novi Sad)

Abstract

This paper researches the size of volatility transmission from Brent oil market to six stock markets of Central and Eastern European countries, with a distinction between the short-term and long-term effect. We create the transitory and permanent parts of volatilities by using the component GARCH model with the optimal density function and inserted dummy variables. Created volatilities are subsequently embedded in the robust quantile regression framework. The results indicate that the transitory volatility shocks are higher than the permanent ones, which means that investors who operate in the short-term horizons need to be more careful for volatility spillovers from oil market than long-term investors. We find that Polish and Czech stock markets receive the strongest volatility impact from oil. On the other hand, Hungarian and Lithuanian stock markets suffer the lowest volatility effect, in both short and long terms, which favors combining these indices with oil. All the findings can be explained very well by the weight of industry sector in GDP and the net-import of oil. Results of weekly data serve as robustness check for the main findings.

Suggested Citation

  • Dejan Živkov & Marina Gajic-Glamoclija & Jasmina Duraskovic & Mirela Momcilovic, 2022. "Assessing Permanent and Transitory Volatility Spillover Effect from Oil to Stocks in Baltic and Visegrad Countries," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(6), pages 523-542, June.
  • Handle: RePEc:sav:journl:v:70:y:2022:i:6:p:523-542
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    More about this item

    Keywords

    transitory and permanent volatility transmission; Brent oil; stock indices; CGARCH; robust quantile regression;
    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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