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; M. James C.  Crabbe; Lili  Mi; Siyan  Hu; Julien BAKER; Liting  Liu; Kechen Dong

doi:10.3390/jrfm13040066

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, M. James C. Crabbe , Lili Mi, Siyan Hu , Julien BAKER, Liting Liu , Kechen Dong

Department of Sport, Physical Education and Health

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	66
Journal	Journal of Risk and Financial Management
Volume	13
Issue number	4
DOIs	https://doi.org/10.3390/jrfm13040066
Publication status	Published - 3 Apr 2020

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title = "Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China{\textquoteright}s Economy",

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{\textquoteright}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{\textquoteright}s economy will continue to maintain steady development.",

author = "Xiao-Guang Yue and Xue-Feng Shao and Li, {Rita Yi Man} and Crabbe, {M. James C.} and Lili Mi and Siyan Hu and Julien BAKER and Liting Liu and Kechen Dong",

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doi = "10.3390/jrfm13040066",

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AU - Yue, Xiao-Guang

AU - Shao , Xue-Feng

AU - Li, Rita Yi Man

AU - Crabbe , M. James C.

AU - Mi, Lili

AU - Hu , Siyan

AU - BAKER, Julien

AU - Liu , Liting

AU - Dong, Kechen

PY - 2020/4/3

Y1 - 2020/4/3

N2 - 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.

AB - 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.

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DO - 10.3390/jrfm13040066

M3 - Article

VL - 13

JO - Journal of Risk and Financial Management

JF - Journal of Risk and Financial Management

SN - 1911-8066

IS - 4

M1 - 66

ER -

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

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