基于人工神经网络的新冠肺炎疫情对G8国家金融指标的影响

H. Al-Najjar, N. Al-Rousan, Dania Al-Najjar, Hamzeh F. Assous, D. Al-Najjar
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引用次数: 11

摘要

目的:COVID-19大流行病毒已经影响了世界上最大的经济体,全球范围内新冠肺炎确诊和死亡病例不断增加,导致股指每天都不稳定,这些变化导致G8因疫情蔓延而遭受重大损失。本文旨在通过7个封城变量,研究新冠肺炎事件对G8最重要股指的影响,利用国家封城公告对G8最重要股指的影响。设计/方法/方法:本研究采用Pearson相关性来研究国际指数上封城变量的强度,并利用神经网络建立预测模型,该模型可以独立估计股票市场的走势,神经网络采用R2和均方误差(MSE)两个绩效指标。股票指数预测的结果表明,R2值之间的所有G8 0 979和0 990,在MSE 54和604之间的值结果表明,COVID-19事件对股票运动有很强的负面影响,3月的最低点的G8指数之外,美国封锁和利率的变化是最受到八国集团股票交易的影响,其次是德国、法国和英国创意/值:该研究利用人工智能神经网络研究了美国封锁的影响,美国降低利率以及八国集团不同国家宣布封锁©2021,Emerald Publishing Limited
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Impact of COVID-19 pandemic virus on G8 countries’ financial indices based on artificial neural network
Purpose: The COVID-19 pandemic virus has affected the largest economies around the world, especially Group 8 and Group 20 The increasing numbers of confirmed and deceased cases of the COVID-19 pandemic worldwide are causing instability in stock indices every day These changes resulted in the G8 suffering major losses due to the spread of the pandemic This paper aims to study the impact of COVID-19 events using country lockdown announcement on the most important stock indices in G8 by using seven lockdown variables To find the impact of the COVID-19 virus on G8, a correlation analysis and an artificial neural network model are adopted Design/methodology/approach: In this study, a Pearson correlation is used to study the strength of lockdown variables on international indices, where neural network is used to build a prediction model that can estimate the movement of stock markets independently The neural network used two performance metrics including R2 and mean square error (MSE) Findings: The results of stock indices prediction showed that R2 values of all G8 are between 0 979 and 0 990, where MSE values are between 54 and 604 The results showed that the COVID-19 events had a strong negative impact on stock movement, with the lowest point on the March of all G8 indices Besides, the US lockdown and interest rate changes are the most affected by the G8 stock trading, followed by Germany, France and the UK Originality/value: The study has used artificial intelligent neural network to study the impact of US lockdown, decrease the interest rate in the USA and the announce of lockdown in different G8 countries © 2021, Emerald Publishing Limited
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来源期刊
CiteScore
3.40
自引率
4.20%
发文量
17
期刊介绍: The Journal of Chinese Economic and Foreign Trade Studies (JCEFTS) negotiates China''s unique position within the international economy, and its interaction across the globe. From a truly international perspective, the journal publishes both qualitative and quantitative research in all areas of Chinese business and foreign trade, technical economics, business environment and business strategy. JCEFTS publishes high quality research papers, viewpoints, conceptual papers, case studies, literature reviews and general views. Emphasis is placed on the publication of articles which seek to link theory with application, or critically analyse real situations in terms of Chinese economics and business in China, with the objective of identifying good practice in these areas and assisting in the development of more appropriate arrangements for addressing crucial issues of Chinese economics and business. Papers accepted for publication will be double–blind peer-reviewed to ensure academic rigour and integrity.
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