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新冠疫情对二十国集团国家股票市场表现的影响:基于长短期记忆循环神经网络方法的证据

The Impact of the COVID-19 Pandemic on Stock Market Performance in G20 Countries: Evidence from Long Short-Term Memory with a Recurrent Neural Network Approach.

作者信息

Fitriana Pingkan Mayosi, Saputra Jumadil, Halim Zairihan Abdul

机构信息

Department of Economics, Faculty of Business, Economics, and Social Development, Universiti Malaysia Terengganu, Terengganu, Malaysia.

出版信息

Big Data. 2025 Jun;13(3):219-242. doi: 10.1089/big.2023.0015. Epub 2023 Dec 20.


DOI:10.1089/big.2023.0015
PMID:38117613
Abstract

In light of developing and industrialized nations, the G20 economies account for a whopping two-thirds of the world's population and are the largest economies globally. Public emergencies have occasionally arisen due to the rapid spread of COVID-19 globally, impacting many people's lives, especially in G20 countries. Thus, this study is written to investigate the impact of the COVID-19 pandemic on stock market performance in G20 countries. This study uses daily stock market data of G20 countries from January 1, 2019 to June 30, 2020. The stock market data were divided into G7 countries and non-G7 countries. The data were analyzed using Long Short-Term Memory with a Recurrent Neural Network (LSTM-RNN) approach. The result indicated a gap between the actual stock market index and a forecasted time series that would have happened without COVID-19. Owing to movement restrictions, this study found that stock markets in six countries, including Argentina, China, South Africa, Turkey, Saudi Arabia, and the United States, are affected negatively. Besides that, movement restrictions in the G7 countries, excluding the United States, and the non-G20 countries, excluding Argentina, China, South Africa, Turkey, and Saudi, significantly impact the stock market performance. Generally, LSTM prediction estimates relative terms, except for stock market performance in the United Kingdom, the Republic of Korea, South Africa, and Spain. The stock market performance in the United Kingdom and Spain countries has significantly reduced during and after the occurrence of COVID-19. It indicates that the COVID-19 pandemic considerably influenced the stock markets of 14 G20 countries, whereas less severely impacting 6 remaining countries. In conclusion, our empirical evidence showed that the pandemic had restricted effects on the stock market performance in G20 countries.

摘要

就发展中国家和工业化国家而言,二十国集团(G20)经济体占世界人口的三分之二,是全球最大的经济体。由于新冠病毒在全球迅速传播,公共紧急情况时有发生,影响了许多人的生活,尤其是在G20国家。因此,撰写本研究旨在调查新冠疫情对G20国家股票市场表现的影响。本研究使用了2019年1月1日至2020年6月30日G20国家的每日股票市场数据。股票市场数据分为七国集团(G7)国家和非G7国家。采用带有递归神经网络的长短期记忆(LSTM-RNN)方法对数据进行分析。结果表明,实际股票市场指数与没有新冠疫情时本应出现的预测时间序列之间存在差距。由于行动限制,本研究发现包括阿根廷、中国、南非、土耳其、沙特阿拉伯和美国在内的六个国家的股票市场受到负面影响。此外,除美国外的G7国家以及除阿根廷、中国、南非、土耳其和沙特外的非G20国家的行动限制对股票市场表现有重大影响。一般来说,LSTM预测估计的是相对情况,英国、韩国、南非和西班牙的股票市场表现除外。在新冠疫情期间及之后,英国和西班牙的股票市场表现大幅下降。这表明新冠疫情对14个G20国家的股票市场产生了重大影响,而对其余6个国家的影响较小。总之,我们的实证证据表明,疫情对G20国家的股票市场表现产生了限制性影响。

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