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COVID-19 Pandemic & Financial Market Volatility; Evidence from GARCH Models

Author

Listed:
  • Maaz Khan

    (Department of Management Sciences, COMSATS University Islamabad, Islamabad 45550, Pakistan)

  • Umar Nawaz Kayani

    (College of Business, Al Ain University, Abu Dhabi P.O. Box 122612, United Arab Emirates)

  • Mrestyal Khan

    (Department of Management Sciences, Balochistan University of Information Technology, Engineering & Management Sciences (BUITEMS), Quetta 87300, Pakistan)

  • Khurrum Shahzad Mughal

    (Islamabad Policy Research Institute—IPRI, Islamabad 45710, Pakistan)

  • Mohammad Haseeb

    (China Institute of Development Strategy and Planning, and Center for Industrial Economics, Wuhan University, Wuhan 430072, China)

Abstract

Across the globe, COVID-19 has disrupted the financial markets, making them more volatile. Thus, this paper examines the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1, 1), and EGARCH (1, 1) econometric models on the daily time series returns data ranging from 27 November 2018 to 15 June 2021. The empirical findings show a high level of volatility persistence in all the financial markets during the COVID-19 pandemic. Moreover, the Crude Oil and S&P 500 index shows significant positive asymmetric behavior during the pandemic. Apart from this, the results also reveal that EGARCH is the most appropriate model to capture the volatilities of the financial markets before the COVID-19 pandemic, whereas during the COVID-19 period and for the whole period, each GARCH family evenly models the volatile behavior of the six financial markets. This study provides financial investors and policymakers with useful insight into adopting effective strategies for constructing portfolios during crises in the future.

Suggested Citation

  • Maaz Khan & Umar Nawaz Kayani & Mrestyal Khan & Khurrum Shahzad Mughal & Mohammad Haseeb, 2023. "COVID-19 Pandemic & Financial Market Volatility; Evidence from GARCH Models," JRFM, MDPI, vol. 16(1), pages 1-20, January.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:1:p:50-:d:1034318
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    References listed on IDEAS

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    2. Lihua Liu & Yuping Chen & Wei Li & Yanfang Zeng & Mingshui Lin, 2023. "Research on Industry Transformation Models and Influencing Factors of Hot Spring Villages from the Perspective of Sustainable Development: A Case Study of Fujian, China," Sustainability, MDPI, vol. 15(13), pages 1-19, June.

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