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Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash

Author

Listed:
  • Kamel Si Mohammed

    (UBBAT - Université Ain Temouchent Belhadj Bouchaib = Ain Temouchent University Belhadj Bouchaib)

  • Marco Tedeschi

    (UNIVPM - Polytechnic University of Marche / Università Politecnica delle Marche)

  • Sabrine Mallek

    (ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)

  • Małgorzata Tarczyńska-Łuniewska

    (University of Szczecin)

  • Anqi Zhang

    (Shanghai University)

Abstract

This study aims to investigate the dynamic relationship between oil prices and stock markets in the G5+ countries using Parkinson's proximal realized volatility. We separate positive and negative semi-variance to compute asymmetric aggregate static spillovers according to the Diebold and Yilmaz (DY) approach. Moreover, we use a Quantile VAR to investigate the behavior of series in different quantiles corresponding to different market scenarios. Consistently with the literature concerns, we use a daily sample of market indices prices with the Brent oil price from June 1, 2017, to July 2, 2022. We found an asymmetric linkage between oil prices and the stock market, which has significant implications for portfolio hedging strategies. Specifically, our research indicates that the impact of the Russian-Ukrainian conflict on the energy crisis has been significantly higher than that of the COVID-19 pandemic, especially in the short term. However, we observe a higher persistence of negative spillovers for COVID-19 compared to those recorded during the Russia-Ukraine war. From a methodological viewpoint, this result enforces the choice of an asymmetric model to investigate the volatility transmission between financial market series. Finally, we found crude oil to emit volatility spillovers in quantiles above 80%. This result emphasizes the instability perceived in crude oil price when general market volatility increase. Quite the opposite, about one-third of oil price shocks, are linked to the national stock exchange uncertainty in low and middle quantiles, underlining the investors' dependency on this commodity. These results have important implications for policymakers and institutional authorities, who must consider the changing macroeconomic environment and reduce dependence on Russian energy.

Suggested Citation

  • Kamel Si Mohammed & Marco Tedeschi & Sabrine Mallek & Małgorzata Tarczyńska-Łuniewska & Anqi Zhang, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Post-Print hal-04315164, HAL.
  • Handle: RePEc:hal:journl:hal-04315164
    DOI: 10.1016/j.resourpol.2023.103798
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    Cited by:

    1. Zhang, Feipeng & Gao, Hongfu & Yuan, Di, 2024. "The asymmetric effect of G7 stock market volatility on predicting oil price volatility: Evidence from quantile autoregression model," Journal of Commodity Markets, Elsevier, vol. 35(C).
    2. Cui, Jinxin & Maghyereh, Aktham, 2024. "Unveiling interconnectedness: Exploring higher-order moments among energy, precious metals, industrial metals, and agricultural commodities in the context of geopolitical risks and systemic stress," Journal of Commodity Markets, Elsevier, vol. 33(C).
    3. Cifuentes-Faura, Javier & Mohammed, Kamel Si & Alofaysan, Hind, 2024. "The connectedness and structural changes among green and conventional energy markets with CO2 emissions in the United States," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 80-94.
    4. Yousfi, Mohamed & Farhani, Ramzi & Bouzgarrou, Houssam, 2024. "From the pandemic to the Russia–Ukraine crisis: Dynamic behavior of connectedness between financial markets and implications for portfolio management," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1178-1197.
    5. Doğan, Buhari & Radulescu, Magdalena & Nassani, Abdelmohsen A. & Mohammed, Kamel S.I. & Benlagha, Noureddine & Baldan, Cristina Florentina, 2025. "Spillovers across the crude oil and major currencies exchange rates using dynamic-quantile-frequency analysis," International Review of Economics & Finance, Elsevier, vol. 99(C).
    6. Wang, Kai-Hua & Wen, Cui-Ping & Xu, Bao-Chang & Li, Xin, 2024. "Receiver or transmitter? Unlocking the role of green technology innovation in sustainable development, energy, and carbon markets," Technology in Society, Elsevier, vol. 79(C).
    7. Li, Xiafei & Yang, Shuangpeng & Luo, Keyu & Liang, Chao, 2024. "Spillover relationships between international crude oil markets and global energy stock markets under the influence of geopolitical risks: New evidence," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    8. Amar Rao & Marco Tedeschi & Kamel Si Mohammed & Umer Shahzad, 2024. "Role of Economic Policy Uncertainty in Energy Commodities Prices Forecasting: Evidence from a Hybrid Deep Learning Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3295-3315, December.
    9. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2024. "Extreme risk contagions among fossil energy companies in China: Insights from a multilayer dynamic network analysis," Energy, Elsevier, vol. 306(C).
    10. Bouteska, A. & Rahman, Mashuk & Hassan, M. Kabir & Sanchez, Benito A., 2025. "Re-examining the nexus between Chinese carbon markets with energy and non-energy commodity markets in a novel risk spillover network approach," Pacific-Basin Finance Journal, Elsevier, vol. 92(C).
    11. Han, SeungOh, 2025. "Dynamic hedging strategies for U.S. investors in international stock ETFs following geopolitical conflicts," Finance Research Letters, Elsevier, vol. 72(C).
    12. Marina Yu. Malkina, 2024. "Financial contagion in the US, European and Chinese stock markets during global shocks," Journal of New Economy, Ural State University of Economics, vol. 25(4), pages 47-67, December.
    13. Mensi, Walid & Gök, Remzi & Gemici, Eray & Vo, Xuan Vinh & Kang, Sang Hoon, 2025. "Extreme dependence, connectedness, and causality between US sector stocks and oil shocks," International Review of Economics & Finance, Elsevier, vol. 98(C).
    14. Charalampos Basdekis & Apostolos G. Christopoulos & Ioannis Katsampoxakis & Stylianos Xanthopoulos, 2024. "Trends and Challenges after the Impact of COVID-19 and the Energy Crisis on Financial Markets," Energies, MDPI, vol. 17(15), pages 1-14, August.
    15. Marina Yu. Malkina, 2024. "Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 452-475.
    16. Just, Małgorzata & Kliber, Agata & Echaust, Krzysztof, 2025. "Return connectedness between energy commodities and stock markets: New evidence from 31 energy sector companies in Europe," International Review of Financial Analysis, Elsevier, vol. 103(C).

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    Keywords

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G1 - Financial Economics - - General Financial Markets

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