Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy

Yue, X-G; Shao, X-F; Li, RYM; Crabbe, MJC; Mi, L; Hu, S; Baker, JS; Liu, L; Dong, K

Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy

Yue, X-G Shao, X-F Li, RYM Crabbe, MJC Mi, L Hu, S Baker, JS Liu, L Dong, K

Permalink

Publisher:: MDPI AG
Publication Type:: Journal Article
Citation:: Journal of Risk and Financial Management, 2020, 13, (4), pp. 66
Issue Date:: 2020-04-03

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Download Published versionAdobe PDF (5.22 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Yue, X-G
dc.contributor.author	Shao, X-F
dc.contributor.author	Li, RYM
dc.contributor.author	Crabbe, MJC
dc.contributor.author	Mi, L
dc.contributor.author	Hu, S
dc.contributor.author	Baker, JS
dc.contributor.author	Liu, L
dc.contributor.author	Dong, K
dc.date.accessioned	2022-07-04T04:00:23Z
dc.date.available	2022-07-04T04:00:23Z
dc.date.issued	2020-04-03
dc.identifier.citation	Journal of Risk and Financial Management, 2020, 13, (4), pp. 66
dc.identifier.issn	1911-8066
dc.identifier.issn	1911-8074
dc.identifier.uri	http://hdl.handle.net/10453/158601
dc.description.abstract	<jats:p>This study first analyzes the national and global infection status of the Coronavirus Disease that emerged in 2019 (COVID-19). It then uses the trend comparison method to predict the inflection point and Key Point of the COVID-19 virus by comparison with the severe acute respiratory syndrome (SARS) graphs, followed by using the Autoregressive Integrated Moving Average model, Autoregressive Moving Average model, Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors, and Holt Winter’s Exponential Smoothing to predict infections, deaths, and GDP in China. Finally, it discusses and assesses the impact of these results. This study argues that even if the risks and impacts of the epidemic are significant, China’s economy will continue to maintain steady development.</jats:p>
dc.language	en
dc.publisher	MDPI AG
dc.relation.ispartof	Journal of Risk and Financial Management
dc.relation.isbasedon	10.3390/jrfm13040066
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy
dc.type	Journal Article
utslib.citation.volume	13
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	open_access	*
dc.date.updated	2022-07-04T04:00:21Z
pubs.issue	4
pubs.publication-status	Published online
pubs.volume	13
utslib.citation.issue	4

Abstract:

This study first analyzes the national and global infection status of the Coronavirus Disease that emerged in 2019 (COVID-19). It then uses the trend comparison method to predict the inflection point and Key Point of the COVID-19 virus by comparison with the severe acute respiratory syndrome (SARS) graphs, followed by using the Autoregressive Integrated Moving Average model, Autoregressive Moving Average model, Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors, and Holt Winter’s Exponential Smoothing to predict infections, deaths, and GDP in China. Finally, it discusses and assesses the impact of these results. This study argues that even if the risks and impacts of the epidemic are significant, China’s economy will continue to maintain steady development.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/158601