Network analysis of global stock markets at the beginning of the coronavirus disease (Covid-19) outbreak

Abstract

The Coronavirus (COVID-19) outbreak has become one of the biggest threats to the global economy and financial markets. This study aims to analyze the effects of COVID-19 on 56 global stock indices from October 15, 2019 to August 7, 2020 by using a complex network method. Furthermore, the change of the network structure is analyzed in depth by dividing the stock markets into developed, emerging and frontier markets. The findings reveal a structural change in the form of node changes, reduced connectivity and significant differences in the topological characteristics of the network, due to COVID-19. A contagion effect is also identified in the network structure of emerging markets, with the nodes behaving synchronously. The findings also reveal substantial clustering and homogeneity in the world stock market network, based on geographic positioning. Besides, the number of positive correlations in the global stock indices increased during the outbreak. The stock markets of France and Germany seem to be the most relevant developed markets, while Taiwan and Slovenia have this relevance in emerging and frontier markets. The findings of this study help regulators and practitioners to design important strategies in the light of varying stock market dynamics during COVID-19.

Keywords

• COVID-19
• Network
• Minimum spanning tree
• Network topology
• Stock markets