Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/334103 
Year of Publication: 
2023
Citation: 
[Journal:] Asian Journal of Economics and Banking (AJEB) [ISSN:] 2633-7991 [Volume:] 7 [Issue:] 3 [Year:] 2023 [Pages:] 310-332
Publisher: 
Emerald, Leeds
Abstract: 
Purpose - Unlimited quantitative easing (QE) is one of the monetary policies used to stimulate the economy during the coronavirus disease 2019 (COVID-19) pandemic. This policy has affected the financial markets worldwide. This empirical research aims at studying the dependence among stock markets before and after unlimited QE announcements. Design/methodology/approach - The copula-based GARCH (1,1) and minimum spanning tree models are used in this study to analyze 14 series of stock market data, on 6 ASEAN and 8 other countries outside the region. The data are divided into two periods to compare the differences in dependence. Findings - The findings show changes in dependence among the volatility of daily returns in 14 stock markets during each period. After the unlimited QE announcement, the upper tail dependence became more apparent, while the role of the lower tail dependence was reduced. The minimum spanning tree can show the close relationships between stock markets, indicating changes in the connection network after the announcement. Originality/value - This study allows the dependency to be compared between stock market volatility before and after the announcement of unlimited QE during the COVID-19 pandemic. Moreover, the study fills the literature gap by combining the copula-based GARCH and the minimum spanning tree models to analyze and reveal the systemic network of the relationships.
Subjects: 
Copula
COVID-19 pandemic
GARCH
Network analysis
QE
Stock markets
JEL: 
C220
C440
C460
G150
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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