Global Stock Markets Volatility Correlation Structure and Implication of Portfolio Based on Complex Network Theory

Peng Yang (), Zhenzhang Hu (), Sheng Luo (), Ke Huang () and Qiumei Li ()
Additional contact information
Peng Yang: Institute of Industrial Economics Guangxi Academy of Social Sciences
Zhenzhang Hu: Guangxi Zhishang Digital Technology Co., Ltd
Sheng Luo: Guangxi University of Finance and Economics
Ke Huang: Nanning University
Qiumei Li: Guangxi University of Finance and Economics

Computational Economics, 2025, vol. 66, issue 3, No 13, 2169-2198

Abstract: Abstract This paper constructs the volatility network of stock price indices in 49 countries, taking the COVID-19 event as an external shock to examine the impact of major emergencies on the volatility network of stock indices, the risk transmission mechanism across borders and the characteristics of key nodes. We further analyze the centrality of the network theory and empirical mechanism of the optimal portfolio weighting under the “mean–variance” framework while extending the results to portfolio risk management scenarios. The key findings are the impact of COVID-19 has led to a significant increase in convergence in the behavioral patterns of main countries stock indexes, changes in volatility network nodes and significant differences in topological structure characteristics. Compared with markets of emerging countries, the stock indexes in developed markets show the highest correlation before and after the epidemic. The main countries stock indexes volatility network based on geographic distribution reflects the characteristics of clustering and homogeneity. The stock indexes of few countries, such as Singapore, France, Germany, and the Netherlands, are the key market and source of market risk during the outbreak. Under the “mean–variance” framework, theoretical and empirical analysis shows that the optimal portfolio is more inclined to allocate more weight to stock indexes with low centrality, low volatility, and high Sharpe ratio. Because the marginal asset portfolio with less centrality is more conducive to reducing the overall risk of the asset portfolio. The main research objective of this paper is to provide financial regulators and financial practitioners with relevant ideas and strategies for inter-country portfolio risk management under major emergencies, and to provide important insights for them to understand the correlation structure and risk transfer characteristics of the global stock indexes of main countries under the impact of major emergencies, and for market participants to optimize their portfolio structure and manage portfolio risks.

Keywords: Global stock markets; Volatility network; Portfolio; “Mean–variance” (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-024-10771-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:66:y:2025:i:3:d:10.1007_s10614-024-10771-6

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-024-10771-6

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().