Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy
by
Xiao-Guang Yue 1,2,3
, Xue-Feng Shao 4,*, Rita Yi Man Li 5, M. James C. Crabbe 6,7,8, Lili Mi 9, Siyan Hu 10,*, Julien S Baker 11, Liting Liu 12 and Kechen Dong 13
Xiao-Guang Yue 1,2,3, Xue-Feng Shao 4,*, Rita Yi Man Li 5, M. James C. Crabbe 6,7,8, Lili Mi 9, Siyan Hu 10,*, Julien S Baker 11, Liting Liu 12 and Kechen Dong 13
1
Department of Computer Science and Engineering, School of Sciences, European University Cyprus, Nicosia 1516, Cyprus
2
Center for Research and Innovation in Business Sciences and Information Systems, Polytechnic Institute of Porto, 4610-156 Felgueiras, Portugal
3
Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Nakhon Pathom 73170, Thailand
4
Discipline of International Business, University of Sydney, Sydney, NSW 2006, Australia
5
Department of Economics and Finance, HKSYU Real Estate and Economics Research Lab, Sustainable Real Estate Research Center, Hong Kong Shue Yan University, Hong Kong 999077, China
6
Wolfson College, Oxford University, Oxford OX2 6UD, UK
7
Institute of Biomedical and Environmental Science and Technology, University of Bedfordshire, Luton LU1 3JU, UK
8
School of Life Science, Shanxi University, Taiyuan 030006, China
9
Department of Business Strategy and Innovation, Griffith Business School, Griffith University, Brisbane, QLD 4111, Australia
10
International Engineering and Technology Institute, Hong Kong 999077, China
11
Centre for Health and Exercise Science Research, Department of Sport, Physical Education and Health, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
12
Department of Soil Science, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
13
Adelaide Business School, the University of Adelaide, Adelaide, SA 5000, Australia
*
Authors to whom correspondence should be addressed.
J. Risk Financial Manag. 2020, 13(4), 66; https://doi.org/10.3390/jrfm13040066
Received: 13 February 2020 / Revised: 23 March 2020 / Accepted: 30 March 2020 / Published: 3 April 2020
(This article belongs to the Special Issue COVID-19’s Risk Management and Its Impact on the Economy)
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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Keywords:
COVID-19; China’s economy; severe acute respiratory syndrome; GDP; autoregressive moving average model; autoregressive integrated moving average model; seasonal autoregressive integrated moving-average with exogenous regressors; Holt Winter’s exponential smoothing
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MDPI and ACS Style
Yue, X.-G.; Shao, X.-F.; Li, R.Y.M.; Crabbe, M.J.C.; Mi, L.; Hu, S.; Baker, J.S.; Liu, L.; Dong, K. Risk Prediction and Assessment: Duration, Infections, and Death Toll of the COVID-19 and Its Impact on China’s Economy. J. Risk Financial Manag. 2020, 13, 66.
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