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

المؤلفAl-Maadid, Alanoud
المؤلفAlhazbi, Saleh
المؤلفAl-Thelaya, Khaled
تاريخ الإتاحة2023-01-17T06:57:08Z
تاريخ النشر2022
اسم المنشورResearch in International Business and Finance
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1016/j.ribaf.2022.101667
معرّف المصادر الموحدhttp://hdl.handle.net/10576/38497
الملخصCOVID-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
راعي المشروعThe authors would like to thank Qatar University for financial support , Grant no. QUCP-CBE-2018-1 . The findings are solely the responsibility of the authors.
اللغةen
الناشرElsevier
الموضوعCOVID-19
GCC
Machine-learning
STOCK MARKETS
العنوانUsing machine learning to analyze the impact of coronavirus pandemic news on the stock markets in GCC countries
النوعArticle
رقم المجلد61
dc.accessType Open Access


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