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    Using machine learning to analyze the impact of coronavirus pandemic news on the stock markets in GCC countries

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    1-s2.0-S0275531922000551-main.pdf (1.818Mb)
    Date
    2022
    Author
    Al-Maadid, Alanoud
    Alhazbi, Saleh
    Al-Thelaya, Khaled
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    Abstract
    COVID-19 has resulted in high volatility in financial markets across the world. The goal of this study is to investigate the impact of COVID-19-related news on the stock markets in Gulf Cooperation Council (GCC) countries. The study utilizes machine learning approaches to assess the role of COVID-19 news in stock return predictability in these markets. The results reveal that the stock markets in the United Arab Emirates (UAE), Qatar, Saudi Arabia, and Oman were impacted by coronavirus-related news; however, this news had no impact on the stocks in Bahrain. Moreover, the results indicate that the impacted markets were influenced differently in terms of the quantities and types of news. 2022 The Authors
    DOI/handle
    http://dx.doi.org/10.1016/j.ribaf.2022.101667
    http://hdl.handle.net/10576/38497
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    • Computer Science & Engineering [‎1696‎ items ]
    • COVID-19 Research [‎436‎ items ]
    • Finance & Economics [‎291‎ items ]

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