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COVID-19 大流行与股票市场稳定:部门分析方法。

COVID-19 pandemic and stability of stock market-A sectoral approach.

机构信息

Department of Financial Management, Faculty of Economic Sciences and Management, Nicolaus Copernicus University in Torun, Torun, Poland.

Department of Applied Informatics and Mathematics in Economics, Faculty of Economic Sciences and Management, Nicolaus Copernicus University in Torun, Torun, Poland.

出版信息

PLoS One. 2021 May 20;16(5):e0250938. doi: 10.1371/journal.pone.0250938. eCollection 2021.

Abstract

The COVID-19 pandemic seems to be the most important phenomenon observed from March 2020 in virtually all countries of the world. The necessity to prevent the spread of COVID-19 and keep health care systems efficient resulted in the forced, drastic limitation of economic activity. Many service sectors were hit particularly hard with this but industry and agriculture were also affected. In particular, the pandemic substantially influenced financial markets and we can observe that some markets or instruments vary in stability since they have been affected in the different degree. In the paper, we present the problem of stability of stock markets during the COVID-19 pandemic. Due to the low number of works related to CEE countries during the pandemic, we analyze the Warsaw Stock Exchange, which is one of the most important markets in the CEE. Our main goal was to find how various industries represented by stock market indices have reacted to the COVID-19 shock and consequently which sectors turned out to keep stability and remained resistant to the pandemic. In our investigation, we use two clustering methods: the K-means and the Ward techniques with the criterion of maximizing the silhouette coefficient and six indicators describing stability in terms of profitability, volume, overbought/oversold conditions and volatility. The results of the research present that during the pandemic it was possible to identify 5 clusters of sector indices in the short term and 4 in the medium term. We found that the composition of the clusters is quite stable over time and that none of the obtained clusters can be univocally considered the most or the least stable taking into account all the analyzed indicators. However, we showed that the obtained clusters have different stability origins, i.e. they vary from each other in terms of the investigated indicators of stability.

摘要

COVID-19 大流行似乎是 2020 年 3 月以来世界上几乎所有国家观察到的最重要现象。为了防止 COVID-19 的传播并保持医疗保健系统的效率,各国不得不强行大幅限制经济活动。许多服务行业受到了特别严重的打击,但工业和农业也受到了影响。特别是,大流行极大地影响了金融市场,我们可以观察到,由于受到不同程度的影响,一些市场或工具的稳定性有所不同。在本文中,我们提出了 COVID-19 大流行期间股票市场稳定性的问题。由于与大流行期间中东欧国家相关的工作数量较少,我们分析了华沙证券交易所,它是中东欧最重要的市场之一。我们的主要目标是找到代表股票市场指数的各个行业是如何对 COVID-19 冲击做出反应的,从而确定哪些行业保持稳定,对大流行具有抵抗力。在我们的调查中,我们使用了两种聚类方法:K-均值和 Ward 技术,以最大化轮廓系数为标准,并使用了六个指标来描述盈利能力、成交量、超买/超卖状况和波动性方面的稳定性。研究结果表明,在大流行期间,我们可以在短期内识别出 5 个行业指数集群,在中期识别出 4 个。我们发现,随着时间的推移,聚类的组成相当稳定,并且考虑到所有分析的指标,没有一个聚类可以被唯一地认为是最稳定或最不稳定的。然而,我们表明,所得到的聚类具有不同的稳定性来源,即它们在稳定性的调查指标方面彼此不同。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2638/8136637/62ca5cfc756b/pone.0250938.g001.jpg

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