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Effects of Crude Oil Price Shocks on Stock Markets and Currency Exchange Rates in the Context of Russia-Ukraine Conflict: Evidence from G7 Countries


  • Bhaskar Bagchi

    (Department of Commerce, University of Gour Banga, Malda 732103, India)

  • Biswajit Paul

    (Department of Commerce, University of Gour Banga, Malda 732103, India)


The present study examines the effects of the steep surge in crude oil prices which has also been considered as an oil price shock on the stock price returns and currency exchange rates of G7 countries, namely Canada, France, Germany, Italy, Japan, the United Kingdom (UK) and the United States (US), in the context of the Russia–Ukraine conflict. Due to the outbreak of the war, the steep surge in Brent crude oil price returns is seen as an exogenous shock to stock price returns and exchange rates during the period from 2 January 2017 to 29 June 2022. The paper applies the Fractionally Integrated GARCH (FIGARCH) model to capture the effect of the crude oil price shock and the Breakpoint unit root test to examine the structural breaks in the dataset. Structural breakpoints in the dataset for the entire stock price returns and exchange rates are observed during the period commencing from the last week of February, 2022, to the last week of March, 2022. Except for TSX, NASDAQ and USD, noteworthy long memory effects running from Brent crude oil price to all the stock price returns along with the currency exchange rates for all G7 countries were also found.

Suggested Citation

  • Bhaskar Bagchi & Biswajit Paul, 2023. "Effects of Crude Oil Price Shocks on Stock Markets and Currency Exchange Rates in the Context of Russia-Ukraine Conflict: Evidence from G7 Countries," JRFM, MDPI, vol. 16(2), pages 1-18, January.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:2:p:64-:d:1045044

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    References listed on IDEAS

    1. Christian Conrad & Berthold R. Haag, 2006. "Inequality Constraints in the Fractionally Integrated GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 413-449.
    2. Roubaud, David & Arouri, Mohamed, 2018. "Oil prices, exchange rates and stock markets under uncertainty and regime-switching," Finance Research Letters, Elsevier, vol. 27(C), pages 28-33.
    3. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    4. Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
    5. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    6. Wen, Fenghua & Zhang, Minzhi & Xiao, Jihong & Yue, Wei, 2022. "The impact of oil price shocks on the risk-return relation in the Chinese stock market," Finance Research Letters, Elsevier, vol. 47(PB).
    7. David Bourghelle & Fredj Jawadi & Philippe Rozin, 2021. "Oil price volatility in the context of Covid-19," International Economics, CEPII research center, issue 167, pages 39-49.
    8. Dai, Zhifeng & Peng, Yongxin, 2022. "Economic policy uncertainty and stock market sector time-varying spillover effect: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    9. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
    10. Tian, Meiyu & Li, Wanyang & Wen, Fenghua, 2021. "The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    11. Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
    12. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    13. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Modeling the frequency dynamics of spillovers and connectedness between crude oil and MENA stock markets with portfolio implications," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 397-419.
    14. Nusair, Salah A. & Olson, Dennis, 2022. "Dynamic relationship between exchange rates and stock prices for the G7 countries: A nonlinear ARDL approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    15. Cai, Yifei & Zhang, Dongna & Chang, Tsangyao & Lee, Chien-Chiang, 2022. "Macroeconomic outcomes of OPEC and non-OPEC oil supply shocks in the euro area," Energy Economics, Elsevier, vol. 109(C).
    16. Ahmad, Wasim & Prakash, Ravi & Uddin, Gazi Salah & Chahal, Rishman Jot Kaur & Rahman, Md. Lutfur & Dutta, Anupam, 2020. "On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?," Energy Economics, Elsevier, vol. 91(C).
    17. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
    18. Mengting Jiang & Dongmin Kong, 2021. "The Impact of International Crude Oil Prices on Energy Stock Prices - Evidence From China," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 2(4), pages 1-4.
    19. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    20. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2017. "Explaining the time-varying effects of oil market shocks on US stock returns," Economics Letters, Elsevier, vol. 155(C), pages 84-88.
    21. Chen, Lin & Wen, Fenghua & Li, Wanyang & Yin, Hua & Zhao, Lili, 2022. "Extreme risk spillover of the oil, exchange rate to Chinese stock market: Evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 107(C).
    22. Ali, Syed Riaz Mahmood & Mensi, Walid & Anik, Kaysul Islam & Rahman, Mishkatur & Kang, Sang Hoon, 2022. "The impacts of COVID-19 crisis on spillovers between the oil and stock markets: Evidence from the largest oil importers and exporters," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 345-372.
    23. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    24. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    25. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    26. Zhang, Zitao & Qin, Yun, 2022. "Study on the nonlinear interactions among the international oil price, the RMB exchange rate and China's gold price," Resources Policy, Elsevier, vol. 77(C).
    27. Davidson, James, 2004. "Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 16-29, January.
    28. Yuan, Di & Li, Sufang & Li, Rong & Zhang, Feipeng, 2022. "Economic policy uncertainty, oil and stock markets in BRIC: Evidence from quantiles analysis," Energy Economics, Elsevier, vol. 110(C).
    29. Ma, Richie Ruchuan & Xiong, Tao & Bao, Yukun, 2021. "The Russia-Saudi Arabia oil price war during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 102(C).
    30. Wen, Danyan & Liu, Li & Ma, Chaoqun & Wang, Yudong, 2020. "Extreme risk spillovers between crude oil prices and the U.S. exchange rate: Evidence from oil-exporting and oil-importing countries," Energy, Elsevier, vol. 212(C).
    31. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Zheng, ShiYong & Li, Xiao & Li, Juan & Li, Biqing & Hafeez, Muhammad, 2023. "Assessing the COVID-19 impact on economy, health and natural resource prices: An evidence from selected Asian economies," Resources Policy, Elsevier, vol. 87(PB).
    2. Meng, Xin & Yu, Yanni, 2023. "Does the Russia-Ukraine conflict affect gasoline prices?," Energy Economics, Elsevier, vol. 128(C).
    3. Mouna Ben Saad Zorgati, 2023. "Risk Measure between Exchange Rate and Oil Price during Crises: Evidence from Oil-Importing and Oil-Exporting Countries," JRFM, MDPI, vol. 16(4), pages 1-21, April.
    4. Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2023. "EU sectoral stocks amid geopolitical risk, market sentiment, and crude oil implied volatility: An asymmetric analysis of the Russia-Ukraine tensions," Resources Policy, Elsevier, vol. 82(C).

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    G7 countries; crude oil price; stock return; FIGARCH;
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