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COVID-19 contagion and digital finance
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 autoregressi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211562/ https://www.ncbi.nlm.nih.gov/pubmed/33179008 http://dx.doi.org/10.1007/s42521-020-00021-3 |
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author | Agosto, Arianna Giudici, Paolo |
author_facet | Agosto, Arianna Giudici, Paolo |
author_sort | Agosto, Arianna |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7211562 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-72115622020-05-11 COVID-19 contagion and digital finance Agosto, Arianna Giudici, Paolo Digit Finance Short Communication 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. Springer International Publishing 2020-05-11 2020 /pmc/articles/PMC7211562/ /pubmed/33179008 http://dx.doi.org/10.1007/s42521-020-00021-3 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Short Communication Agosto, Arianna Giudici, Paolo COVID-19 contagion and digital finance |
title | COVID-19 contagion and digital finance |
title_full | COVID-19 contagion and digital finance |
title_fullStr | COVID-19 contagion and digital finance |
title_full_unstemmed | COVID-19 contagion and digital finance |
title_short | COVID-19 contagion and digital finance |
title_sort | covid-19 contagion and digital finance |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211562/ https://www.ncbi.nlm.nih.gov/pubmed/33179008 http://dx.doi.org/10.1007/s42521-020-00021-3 |
work_keys_str_mv | AT agostoarianna covid19contagionanddigitalfinance AT giudicipaolo covid19contagionanddigitalfinance |