Al-Maadid Alanoud, Alhazbi Saleh, Al-Thelaya Khaled
College of Economics and Finance, Qatar University, Doha, Qatar.
Department of Computer Science and Engineering, Qatar University, Doha, Qatar.
Res Int Bus Finance. 2022 Oct;61:101667. doi: 10.1016/j.ribaf.2022.101667. Epub 2022 Apr 28.
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.
新冠疫情导致全球金融市场出现高度波动。本研究的目的是调查与新冠疫情相关的新闻对海湾合作委员会（GCC）国家股票市场的影响。该研究利用机器学习方法来评估新冠疫情新闻在这些市场股票回报可预测性方面的作用。结果显示，阿拉伯联合酋长国（UAE）、卡塔尔、沙特阿拉伯和阿曼的股票市场受到了与新冠病毒相关新闻的影响；然而，这类新闻对巴林的股票没有影响。此外，结果表明，受影响的市场在新闻数量和类型方面受到的影响各不相同。
