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During the SARS-CoV-2 (COIVD-19) outbreak, China repeatedly stressed that the response to the pandemic required action at all levels of government, including the issuance of Pandemic Bonds to help the country return to work and production. However, studies on the effectiveness of Pandemic Bonds during that period are rare. Starting with China’s national financial bond market data after COVID-19 in 2020, this paper focuses on the correlation between the Credit Spreads of the relevant bonds and the corresponding bond market rate of return, based on the Copula model. The empirical analysis is also carried out for multiple dimensional groupings such as enterprises, industries, provinces, and bond maturities. The results show that there is a significant positive correlation between the Credit Spreads of Pandemic Bonds and market returns. In addition, the market correlation is higher for Pandemic Bonds issued in Hubei Province, which is at the center of the 2020 pandemic, and the shorter the maturity of the Pandemic Bond issued, the stronger the relationship with market returns. Finally, this paper provides recommendations for financial regulators and policy makers to consider in their decisions on how to build a more resilient financial system under heavy economic, fiscal, and social pressures.


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Pandemic Bonds Issued by the Chinese Government Supported Post-Disaster Recovery from COVID-19 Pandemic

Show Author's information Feng Liu1,3,4,Deli Kong2,Jinhua Kong5Shiying Lu6Zilong Xiao7Qing Xu8Aimin Zhou1,4( )Jiayin Qi3( )
Institute of AI for Education
School of Business and Management, Shanghai International Studies University, Shanghai 201620, China
Institute of Artificial Intelligence and Change Management, Shanghai University of International Business and Economics, Shanghai 200336, China
School of Computer Science and Technology, East China Normal University, Shanghai 200062, China
School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai 201620, China
Department of Economics and Management, Changsha University of Science and Technology, 410000 Changsha, China
Department of Data Science and Computer Science, Sun Yat-sen University, Guangzhou 510080, China
Department of Software, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract

During the SARS-CoV-2 (COIVD-19) outbreak, China repeatedly stressed that the response to the pandemic required action at all levels of government, including the issuance of Pandemic Bonds to help the country return to work and production. However, studies on the effectiveness of Pandemic Bonds during that period are rare. Starting with China’s national financial bond market data after COVID-19 in 2020, this paper focuses on the correlation between the Credit Spreads of the relevant bonds and the corresponding bond market rate of return, based on the Copula model. The empirical analysis is also carried out for multiple dimensional groupings such as enterprises, industries, provinces, and bond maturities. The results show that there is a significant positive correlation between the Credit Spreads of Pandemic Bonds and market returns. In addition, the market correlation is higher for Pandemic Bonds issued in Hubei Province, which is at the center of the 2020 pandemic, and the shorter the maturity of the Pandemic Bond issued, the stronger the relationship with market returns. Finally, this paper provides recommendations for financial regulators and policy makers to consider in their decisions on how to build a more resilient financial system under heavy economic, fiscal, and social pressures.

Keywords: COVID-19, Copula model, Pandemic Bond, Credit Spread

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Publication history

Received: 23 March 2022
Revised: 20 May 2022
Accepted: 30 May 2022
Published: 01 June 2022
Issue date: June 2022

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© The author(s) 2022

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (No. 72042004), the Research Project of Shanghai Science and Technology 26 Commission (No. 20dz2260300), and the Fundamental Research Funds for the Central 27 Universities.

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