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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Al-Maadid, Alanoud, Alhazbi, Saleh, Al-Thelaya, Khaled
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046103/
https://www.ncbi.nlm.nih.gov/pubmed/35502232
http://dx.doi.org/10.1016/j.ribaf.2022.101667
Descripción
Sumario: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.

Ejemplares similares