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The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect

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  • Salisu, Afees A.
  • Ogbonna, Ahamuefula E.

Abstract

In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic. We use hourly data for cryptocurrencies and daily data for the news indicator, thus, the GARCH MIDAS framework which allows for mixed data frequencies is adopted. We validate the presupposition that fear-induced news triggered by the COVID-19 pandemic increases the return volatilities of the cryptocurrencies compared with the period before the pandemic. We also establish that the predictive model that incorporates the news effects forecasts the return volatility better than the benchmark (historical average)model.

Suggested Citation

  • Salisu, Afees A. & Ogbonna, Ahamuefula E., 2022. "The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect," Global Finance Journal, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:glofin:v:54:y:2022:i:c:s1044028321000399
    DOI: 10.1016/j.gfj.2021.100641
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    Cited by:

    1. Nguyen Hong Yen & Le Thanh Ha, 2023. "Interlinkages of cryptocurrency and stock markets during the COVID-19 pandemic by applying a QVAR model," European Journal of Management and Business Economics, Emerald Group Publishing Limited, vol. 33(1), pages 74-95, March.
    2. Xie, Wenhao & Cao, Guangxi, 2024. "Volatility and returns connectedness between cryptocurrency and China’s financial markets: A TVP-VAR extended joint connectedness approach," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    3. Zhou, Fan, 2024. "Cryptocurrency: A new player or a new crisis in financial markets? —— Evolutionary analysis of association and risk spillover based on network science," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 648(C).
    4. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
    5. Walid Mensi & Mariya Gubareva & Hee-Un Ko & Xuan Vinh Vo & Sang Hoon Kang, 2023. "Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    6. Naeem, Muhammad Abubakr & Shahzad, Mohammad Rahim & Karim, Sitara & Assaf, Rima, 2023. "Tail risk transmission in technology-driven markets," Global Finance Journal, Elsevier, vol. 57(C).
    7. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
    8. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    9. Jakub Kubiczek & Marcin Tuszkiewicz, 2022. "Intraday Patterns of Liquidity on the Warsaw Stock Exchange before and after the Outbreak of the COVID-19 Pandemic," IJFS, MDPI, vol. 10(1), pages 1-16, February.

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    More about this item

    Keywords

    Cryptocurrencies; COVID-19; News; GARCH MIDAS;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G01 - Financial Economics - - General - - - Financial Crises
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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