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Oil shocks and stock volatility: new evidence via a Bayesian, graph-based VAR approach

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  • Libo Yin
  • Xiyuan Ma

Abstract

This article examines the temporal dependence between three oil shocks and realized volatility in the stock markets of G20 countries between 1994 and 2019. By applying a novel, graphical, Bayesian VAR (BGVAR) model, we calculate unidirectional linkages of oil and stock volatility with a full and segmented sample. The results suggest an overall causality from stock volatility to oil shocks. For certain short, specific periods, the causal direction reverses. Depending on the country and the source of an oil shock, the magnitude and type of the effect can vary considerably. Specific oil-market shocks occur most often in our full sample. In a time-varying structure, oil supply shocks’ impact on stock volatility is more prominent, and net oil-importing countries’ responses to these shocks are greater than for oil-exporting countries. In addition, we find that relationship dynamics can capture market information, such as global economic growth during the 2008–2009 financial crisis.

Suggested Citation

  • Libo Yin & Xiyuan Ma, 2020. "Oil shocks and stock volatility: new evidence via a Bayesian, graph-based VAR approach," Applied Economics, Taylor & Francis Journals, vol. 52(11), pages 1163-1180, March.
    • Handle: RePEc:taf:applec:v:52:y:2020:i:11:p:1163-1180
    DOI: 10.1080/00036846.2019.1659497
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    Cited by:

    1. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    2. Xu, Xin & Huang, Shupei & An, Haizhong, 2022. "The dynamic moderating function of the exchange rate market on the oil-stock nexus," International Review of Financial Analysis, Elsevier, vol. 81(C).
    3. Alqahtani, Abdullah & Selmi, Refk & Hongbing, Ouyang, 2021. "The financial impacts of jump processes in the crude oil price: Evidence from G20 countries in the pre- and post-COVID-19," Resources Policy, Elsevier, vol. 72(C).
    4. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    5. Zhu, Huiming & Yu, Dongwei & Hau, Liya & Wu, Hao & Ye, Fangyu, 2022. "Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

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