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Risk prediction and assessment: duration, infections, and death toll of the COVID-19 and its impact on China’s economy

  • Xiao-Guang Yue
    ,
  • Xue-Feng Shao
    ,
  • Rita Yi Man Li
    ,
  • James Crabbe
    ,
  • Lili Mi
    ,
  • Siyan Hu
  • Rajamangala University of Technology Rattanakosin
    ,
  • Polytechnic Institute of Porto
    ,
  • European University Cyprus
    ,
  • University of Sydney
    ,
  • Hong Kong Shue Yan University
    ,
  • University of Oxford
Research Output:
Contribution to journal
Article
 Peer-review

Open access

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.

Publication Information

Output type

Research Output:
Contribution to journal
Article
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 66-93

Journal (Volume, Issue Number)

Journal of Risk and Financial Management (Volume 13, Issue 4)

Publication milestones

  • Accepted/In press - 30/03/2020
  • Published - 03/04/2020

Publication status

Published - 03/04/2020

ISSN

1911-8066

Publication IDs

  • handle.net: 10547/623922
  • Scopus: 85085681047

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