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Volatility Contagion Between Crude Oil and G7 Stock Markets in the Light of Trade Wars and COVID-19: A TVP-VAR Extended Joint Connectedness Approach

In: Applications in Energy Finance

Author

Listed:
  • Ioannis Chatziantoniou

    (Hellenic Mediterranean University)

  • Christos Floros

    (Hellenic Mediterranean University)

  • David Gabauer

    (Software Competence Center Hagenberg)

Abstract

We investigate volatility contagion across G7 stock markets and the market for crude oil for the period between 2007 and 2021. Following the work of Balcilar et al. (2021), we utilise the TVP-VAR extended joint connectedness method and compare results to the standard TVP-VAR method that predicates upon the normalisation approach by Diebold and Yılmaz (2009, 2012, 2014). Both methods provide qualitatively similar results. Overall, findings suggest that connectedness in this network is highly responsive to events that greatly affect international financial markets and assume large values across the sample period. Prominent among our results is that the crude oil market is an important net transmitter of volatility shocks across the network during the 2014 oil collapse period. In addition, the period from the beginning of 2018 and until mid-2019 is a rather turbulent period for stock markets a fact which is reflected upon the net receiving character of the market for crude oil. Finally, we show that the Canadian stock market is a persistent net transmitter of volatility in recent years, following developments in international trade and the outbreak of the COVID-19 crisis.

Suggested Citation

  • Ioannis Chatziantoniou & Christos Floros & David Gabauer, 2022. "Volatility Contagion Between Crude Oil and G7 Stock Markets in the Light of Trade Wars and COVID-19: A TVP-VAR Extended Joint Connectedness Approach," Springer Books, in: Christos Floros & Ioannis Chatziantoniou (ed.), Applications in Energy Finance, chapter 0, pages 145-168, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-92957-2_6
    DOI: 10.1007/978-3-030-92957-2_6
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    Citations

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    Cited by:

    1. Guru, Biplab Kumar & Pradhan, Ashis Kumar & Bandaru, Ramakrishna, 2023. "Volatility contagion between oil and the stock markets of G7 countries plus India and China," Resources Policy, Elsevier, vol. 81(C).
    2. Tiwari, Aviral Kumar & Sharma, Gagan Deep & Rao, Amar & Hossain, Mohammad Razib & Dev, Dhairya, 2024. "Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
    3. Sikorska-Pastuszka, Magdalena & Papież, Monika, 2023. "Dynamic volatility connectedness in the European electricity market," Energy Economics, Elsevier, vol. 127(PA).
    4. Cui, Jinxin & Maghyereh, Aktham & Liao, Dijia, 2024. "Risk connectedness between international oil and stock markets during the COVID-19 pandemic and the Russia-Ukraine conflict: Fresh evidence from the higher-order moments," International Review of Economics & Finance, Elsevier, vol. 95(C).

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