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Published on: November 7, 2020
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COVID-19 contagion and digital finance
Arianna Agosto1, Paolo Giudici1
1University of Pavia, Pavia, Italy.
Digital Finance
|November 12, 2020
Summary
The COVID-19 outbreak significantly impacts digital finance. A new statistical model analyzes infection dynamics to anticipate and monitor financial effects, using Poisson autoregression for daily case counts.
Area of Science:
- Epidemiology
- Financial Economics
- Statistical Modeling
Background:
- The COVID-19 pandemic presents unprecedented challenges to global financial systems.
- Digital finance, in particular, is vulnerable to disruptions caused by widespread health crises.
- Understanding disease transmission dynamics is crucial for predicting economic impacts.
Purpose of the Study:
- To develop and present a statistical model for analyzing COVID-19 contagion dynamics.
- To enable anticipation and digital monitoring of the pandemic's impact on digital finance.
- To provide a framework applicable to various countries.
Main Methods:
- Utilized a Poisson autoregression model to analyze daily new observed COVID-19 cases.
- Incorporated both short-term and long-term dependencies in infection count data.
- Applied the model to the time series data of China as a primary case study.
Main Results:
- The model effectively captures the contagion dynamics of COVID-19 in the initial affected country.
- Demonstrated the potential for anticipating and digitally monitoring financial sector impacts.
- Results provide a foundation for broader country-specific analyses.
Conclusions:
- The developed statistical model offers a robust tool for understanding COVID-19's spread.
- This approach can aid in mitigating the adverse effects of the pandemic on digital finance.
- The model's adaptability allows for widespread application in global financial risk assessment.
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