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The Impact of COVID-19 on Gold Price Volatility

Author

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  • Ibrahim Yousef
  • Esam Shehadeh

Abstract

Purpose: This article investigates the implications of the spread of COVID-19 on gold spot prices. Design/Methodology/Approach: We use GARCH and GJR-GARCH models based on daily gold returns over the period 2012-2020 to analyze the impact of the coronavirus on the volatility of gold returns. Findings: We find a positive correlation between the increasing number of global coronavirus cases and increases in gold price. Using GARCH and GJR-GARCH models, we find a significant positive impact of COVID-19 on the conditional variance equation, indicating that the coronavirus may indeed increase the volatility of gold returns. This relates to the fact that the spread of the virus increases uncertainty with regard to the future of economic and financial markets, causing the demand for gold to increase and in turn pushing prices upwards, a trend which may be likely to continue until a vaccine or other treatments begin to stabilize the global economic outlook. Practical Implications: The issue of volatility is of significant concern to both investors and policymakers who base decisions on the relative stability of both individual financial markets and the world economy. Furthermore, volatility estimation is an essential factor in many models and has broad application to the market risk management practices of firms. Finally, understanding the volatility of the gold market is crucial for any analysis of current and future expectations regarding the risks associated with coronavirus which apply to global markets. Originality/Value: The lockdown restrictions which have been widely implemented across the globe to curb the spread of the virus have included travel prohibitions and border closures, stay-at-home and work-from-home orders, and extensive business closures, all causing immense fallout for the global economy. In the current study, we analyze for the first time the impact of the coronavirus on gold spot prices by examining their correlation with the number of cumulative global cases and daily new cases.

Suggested Citation

  • Ibrahim Yousef & Esam Shehadeh, 2020. "The Impact of COVID-19 on Gold Price Volatility," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 353-364.
    • Handle: RePEc:ers:ijebaa:v:viii:y:2020:i:4:p:353-364
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    References listed on IDEAS

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    Cited by:

    1. Jing Niu & Chao Ma & Chun-Ping Chang, 2023. "The arbitrage strategy in the crude oil futures market of shanghai international energy exchange," Economic Change and Restructuring, Springer, vol. 56(2), pages 1201-1223, April.
    2. Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
    3. Herjuna Qobush Izzahdi & Ani Wilujeng Suryani, 2023. "COVID-19 Vaccination, Government Strict Policy and Capital Market Volatility: Evidence from ASEAN Countries," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-135.
    4. Muhammad Saeed & Ijaz Ahmad & Muhammad Ahmad Usman, 2021. "Do the stocks' returns and volatility matter under the COVID-19 pandemic? A Case Study of Pakistan Stock Exchange," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 3(1), pages 13-26, june.
    5. Pierdomenico Duttilo & Stefano Antonio Gattone & Tonio Di Battista, 2021. "Volatility Modeling: An Overview of Equity Markets in the Euro Area during COVID-19 Pandemic," Mathematics, MDPI, vol. 9(11), pages 1-18, May.
    6. Xu, Qingqing & Meng, Tianci & Sha, Yue & Jiang, Xia, 2022. "Volatility in metallic resources prices in COVID-19 and financial Crises-2008: Evidence from global market," Resources Policy, Elsevier, vol. 78(C).
    7. Syed Moudud-Ul-Huq & Md. Shahriar Rahman, 2025. "Stock Market Efficiency of the BRICS Countries Pre-, During, and Post Covid-19 Pandemic: A Multifractal Detrended Fluctuation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1643-1705, March.
    8. Yang, Mo & Wang, Ruotong & Zeng, Zixun & Li, Peizhi, 2024. "Improved prediction of global gold prices: An innovative Hurst-reconfiguration-based machine learning approach," Resources Policy, Elsevier, vol. 88(C).
    9. Atri, Hanen & Kouki, Saoussen & Gallali, Mohamed imen, 2021. "The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach," Resources Policy, Elsevier, vol. 72(C).

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    More about this item

    Keywords

    Coronavirus; gold price; gold volatility; GARCH models.;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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