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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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submitted on 2024-04-21, 09:07 and posted on 2024-04-21, 09:08 authored by Alanoud Al-Maadid, Saleh Alhazbi, Khaled Al-Thelaya

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.

Other Information

Published in: Research in International Business and Finance
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.ribaf.2022.101667

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Institution affiliated with

  • Qatar University
  • College of Business and Economics - QU
  • College of Engineering - QU
  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU

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    College of Science and Engineering - HBKU

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