Using machine learning to analyze the impact of coronavirus pandemic news on the stock markets in GCC countries
| Author | Al-Maadid, Alanoud |
| Author | Alhazbi, Saleh |
| Author | Al-Thelaya, Khaled |
| Available date | 2023-01-17T06:57:08Z |
| Publication Date | 2022 |
| Publication Name | Research in International Business and Finance |
| Resource | Scopus |
| 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 |
| Sponsor | The 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. |
| Language | en |
| Publisher | Elsevier |
| Subject | COVID-19 GCC Machine-learning STOCK MARKETS |
| Type | Article |
| Volume Number | 61 |
Check access options
Files in this item
This item appears in the following Collection(s)
-
Computer Science & Engineering [2402 items ]
-
COVID-19 Research [835 items ]
-
Finance & Economics [419 items ]