COVID-19 contagion and digital finance.

Digital finance Pub Date : 2020-01-01 Epub Date: 2020-05-11 DOI:10.1007/s42521-020-00021-3
Arianna Agosto, Paolo Giudici
{"title":"COVID-19 contagion and digital finance.","authors":"Arianna Agosto,&nbsp;Paolo Giudici","doi":"10.1007/s42521-020-00021-3","DOIUrl":null,"url":null,"abstract":"<p><p>Digital finance is going to be heavily affected by the COVID-19 outbreak. We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, so that its impact on finance can possibly be anticipated, and digitally monitored. The model is a Poisson autoregression of the daily new observed cases, and considers both short-term and long-term dependence in the infections counts. Model results are presented for the observed time series of China, the first affected country, but can be easily reproduced for all countries.</p>","PeriodicalId":72817,"journal":{"name":"Digital finance","volume":"2 1-2","pages":"159-167"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s42521-020-00021-3","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s42521-020-00021-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/5/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Digital finance is going to be heavily affected by the COVID-19 outbreak. We present a statistical model which can be employed to understand the contagion dynamics of the COVID-19, so that its impact on finance can possibly be anticipated, and digitally monitored. The model is a Poisson autoregression of the daily new observed cases, and considers both short-term and long-term dependence in the infections counts. Model results are presented for the observed time series of China, the first affected country, but can be easily reproduced for all countries.

Abstract Image

Abstract Image

Abstract Image

COVID-19传染与数字金融。
数字金融将受到新冠肺炎疫情的严重影响。我们提出了一个统计模型,可用于了解COVID-19的传染动态,从而有可能预测其对金融的影响,并进行数字化监测。该模型是每日新观察病例的泊松自回归,并考虑了感染计数的短期和长期依赖性。模型结果是针对第一个受影响的国家中国的观测时间序列给出的,但可以很容易地复制到所有国家。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信