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

被引：7

作者：

Al-Maadid, Alanoud ^{[1
]}

Alhazbi, Saleh ^{[2
,4
]}

Al-Thelaya, Khaled ^{[3
]}

机构：

[1] Qatar Univ, Coll Econ & Finance, Doha, Qatar

[2] Qatar Univ, Dept Comp Sci & Engn, Doha, Qatar

[3] Hamad Bin Khalifa Univ, Coll Sci & Engn, Doha, Qatar

[4] Qatar Univ, POB 2713, Doha, Qatar

来源：

RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE | 2022年 / 61卷

关键词：

COVID-19; Machine-learning; STOCK MARKETS; GCC; RETURNS; LIQUIDITY; RISK;

D O I：

10.1016/j.ribaf.2022.101667

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：14

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