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Dynamic causality interplay from COVID-19 pandemic to oil price, stock market, and economic policy uncertainty: evidence from oil-importing and oil-exporting countries

Author

Listed:
  • Rabeh Khalfaoui

    (FSEG)

  • Sakiru Adebola Solarin

    (School of Economics, University of Notthingham Malaysia)

  • Adel Al-Qadasi

    (Shaqra University
    The Hodeidah University)

  • Sami Ben Jabeur

    (ESDES)

Abstract

In this study we examine the time-varying causal effect of the novel COVID-19 pandemic in the major oil-importing and oil-exporting countries on the oil price changes, stock market volatilities and the economic uncertainty using the wavelet coherence and network analysis. During the period of the pandemic, we explore such relationship by resorting to the wavelet coherence and gaussian graphical model (GGM) frameworks. Wavelet analysis enables us to measure the dynamics of the causal effect of the novel covid-19 pandemic in the time–frequency space. Regarding the findings displayed herein, we first found that the COVID-19 pandemic has a severe influence on oil prices, stock market indices, and the economic uncertainty. Second the intensity of the causality effect is stronger in the longer horizon than in the short ones, suggesting that the causality exercise continues. Our findings also provide evidence that the COVID-19 pandemic and oil price changes in oil-importing countries mirror those in oil-exporting countries and vice versa. Further, the COVID-19 pandemic has a profound immediate time–frequency effect on the US, Japanese, South Korean, Indian, and Canadian economic uncertainties. A better understanding of oil and stock market prices in the oil-importing and oil-exporting countries is vital for investors and policymakers, specially since the novel unprecedented COVID-19 crisis has been recognized among the most serious ever happened. Thus, the findings suggest that the authorities should strongly take efficient actions to minimize risk.

Suggested Citation

  • Rabeh Khalfaoui & Sakiru Adebola Solarin & Adel Al-Qadasi & Sami Ben Jabeur, 2022. "Dynamic causality interplay from COVID-19 pandemic to oil price, stock market, and economic policy uncertainty: evidence from oil-importing and oil-exporting countries," Annals of Operations Research, Springer, vol. 313(1), pages 105-143, June.
    • Handle: RePEc:spr:annopr:v:313:y:2022:i:1:d:10.1007_s10479-021-04446-w
    DOI: 10.1007/s10479-021-04446-w
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    2. Khalfaoui, Rabeh & Stef, Nicolae & Wissal, Ben Arfi & Sami, Ben Jabeur, 2022. "Dynamic spillover effects and connectedness among climate change, technological innovation, and uncertainty: Evidence from a quantile VAR network and wavelet coherence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    3. Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
    4. Mohd Ziaur Rehman & Shabeer Khan & Ghulam Abbas & Mohammed Alhashim, 2023. "Novel COVID-19 Outbreak and Global Uncertainty in the Top-10 Affected Countries: Evidence from Wavelet Coherence Approach," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    5. Umer Shahzad & Muhammad Ramzan & Muhammad Ibrahim Shah & Buhari DoÄŸan & Ahdi Noomen Ajmi, 2022. "Analyzing the Nexus Between Geopolitical Risk, Policy Uncertainty, and Tourist Arrivals: Evidence From the United States," Evaluation Review, , vol. 46(3), pages 266-295, June.
    6. Rabin K. Jana & Aviral Kumar Tiwari & Shawkat Hammoudeh & Claudiu Albulescu, 2022. "Financial modeling, risk management of energy and environmental instruments and derivatives: past, present, and future," Annals of Operations Research, Springer, vol. 313(1), pages 1-7, June.
    7. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
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    More about this item

    Keywords

    COVID-19; Oil price; Stocks; Economic uncertainty; Wavelet analysis; Gaussian graphical model; Value-at-Risk;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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