How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network

ABSTRACT

The recent financial network analysis approach reveals that the topologies of financial markets have an important influence on market dynamics. However, the majority of existing Finance Big Data networks are built as undirected networks without information on the influence directions among prices. Rather than understanding the correlations, this research applies the Granger causality test to build the Granger Causality Directed Network for 33 global major stock market indices. The paper further analyzes how the markets influence one another by investigating the directed edges in the different filtered networks. The network topology that evolves in different market periods is analyzed via a sliding window approach and Finance Big Data visualization. By quantifying the influences of market indices, 33 global major stock markets from the Granger causality network are ranked in comparison with the result based on PageRank centrality algorithm. Results reveal that the ranking lists are similar in both approaches where the U.S. indices dominate the top position followed by other American, European, and Asian indices. The lead-lag analysis reveals that there is lag effects among the global indices. The result sheds new insights on the influences among global stock markets with implications for trading strategy design, global portfolio management, risk management, and markets regulation.

KEY WORDS AND PHRASES:

• Finance Big Data
• Granger causality directed network
• global stock markets
• financial network analysis
• data visualization
• trading strategy
• market regulation
• risk management

Acknowledgments

We gratefully acknowledge all editors and anonymous reviewers for their valuable comments and help, which significantly improved the quality of this work.

Supplemental data

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Additional information

Notes on contributors

Yong Tang

YONG TANG ([email protected]; corresponding author) is an assistant professor in Department of Computer Software and Theory, School of Computer Science and Engineering, and Department of Management Science and E-Commerce, School of Economics and Management at University of Electronic Science and Technology of China. In the past 10 years, Dr. Tang has been an entrepreneur and founder of several IT companies in China providing enterprise applications and e-commerce solutions. He serves as a consultant for governments and companies. He has participated in research projects of Ministries of Science and Technology and of Education, China, and in industry. He has been engaged in interdisciplinary research in e-commerce, information systems, data science, financial engineering, and artificial intelligence. He has published in China Finance Review International, Economic Modelling, Physica A: Statistical Mechanics and its Applications, Journal of Applied Statistics, and other venues.

Jason Jie Xiong

JASON JIE XIONG ([email protected]) is an Assistant Professor of Department of Computer Information Systems & Supply Chain Management, Walker College of Business, Appalachian State University. His research interests include Financial Big Data analysis, IT for Development (IT4D), E-Commerce, and the value of Information Systems. He has published in such journals as China Finance Review International and Physica A: Statistical Mechanics and its Applications, and in the proceedings of such conferences as HICSS, AMCIS, and GlobDev.

Yong Luo

YONG LUO ([email protected]) is an assistant professor in Department of Finance, College of Science at Ningbo University of Technology, China, where he also serves as the department head. Dr. Luo has years of industrial practice experience and currently serves as the research director for investment management companies based in Shanghai. His research interests include Financial Big Data, financial engineering, and algorithmic trading. His work appears in such journals as China Finance Review International, Economic Modelling, Physica A: Statistical Mechanics and its Applications, and Journal of Applied Statistics.

Yi-Cheng Zhang

YI CHENG ZHANG ([email protected]) is a professor in Department of Physics at University of Fribourg, Switzerland. He also serves as the director of Alibaba Research Center for Complexity Sciences at Alibaba Business School, Hangzhou Normal University, and as an academic committee member for the Alibaba Research Institute of Alibaba Group. His research interests include big data, complex networks, and information economy. He has published widely, with over 200 articles in Proceedings of the National Academy of Sciences, Physical Review Letters, Physics Reports, Quantitative Finance, and other journals.