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Volatility Between Oil Prices and Stock Returns of Dow Jones Index: A Bivariate GARCH (BEKK) Approach

In: Advances in Time Series Data Methods in Applied Economic Research

Author

Listed:
  • Dimitrios Kartsonakis Mademlis

    (University of Macedonia)

  • Nikolaos Dritsakis

    (University of Macedonia)

Abstract

The relationship between the oil prices and the stock market has occupied several researchers in recent years. Most papers show that stock markets are affected by oil price fluctuations, with few papers supporting the reverse direction. The causal relationships between stock markets and oil prices depend on symmetric and asymmetric changes in oil prices or focus on the unexpected changes in oil prices. In this paper we employ a bivariate BEKK-GARCH(1,1) model in order to estimate the conditional volatility between the oil prices and the stock market index Dow Jones. We are using daily returns from 21 October 1997 to 31 May 2017. The results of our work showed that there is neither transmission of shocks nor volatility spillover between the two markets. Moreover, it was found that the conditional volatility of the returns for both indices is affected only by their own shocks and their own lagged conditional volatility.

Suggested Citation

  • Dimitrios Kartsonakis Mademlis & Nikolaos Dritsakis, 2018. "Volatility Between Oil Prices and Stock Returns of Dow Jones Index: A Bivariate GARCH (BEKK) Approach," Springer Proceedings in Business and Economics, in: Nicholas Tsounis & Aspasia Vlachvei (ed.), Advances in Time Series Data Methods in Applied Economic Research, chapter 0, pages 209-221, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-02194-8_16
    DOI: 10.1007/978-3-030-02194-8_16
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    Citations

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    Cited by:

    1. Dimitrios Kartsonakis Mademlis & Nikolaos Dritsakis, 2021. "Volatility Forecasting using Hybrid GARCH Neural Network Models: The Case of the Italian Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 11(1), pages 49-60.
    2. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    3. Borg, Elin & Kits, Ilya & Junttila, Juha & Uddin, Gazi Salah, 2022. "Dependence between renewable energy related critical metal futures and producer equity markets across varying market conditions," Renewable Energy, Elsevier, vol. 190(C), pages 879-892.

    More about this item

    Keywords

    BEKK-GARCH model; Oil prices; Stock market; Volatility;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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