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Complexities in financial network topological dynamics: modeling of emerging and developed stock markets

  • Tang, Yong Center of Cyberspace and Security, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China - School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland
  • Xiong, Jason Jie Department of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, Boone, USA
  • Jia, Zi-Yang Department of Computer Science, Rutgers University, Piscataway, USA
  • Zhang, Yi-Cheng Department of Physics, University of Fribourg, Switzerland - Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
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    2018
Published in:
  • Complexity. - 2018, vol. 2018, p. 4680140
English Policy makings and regulations of financial markets rely on a good understanding of the complexity of financial markets. There have been recent advances in applying data-driven science and network theory into the studies of social and financial systems. Financial assets and institutions are strongly connected and influence each other. It is essential to study how the topological structures of financial networks could potentially influence market behaviors. Network analysis is an innovative method to enhance data mining and knowledge discovery in financial data. With the help of complex network theory, the topological network structures of a market can be extracted to reveal hidden information and relationships among stocks. In this study, two major markets of the most influential economies, China and the United States, are systematically studied from the perspective of financial network analysis. Results suggest that the network properties and hierarchical structures are fundamentally different for the two stock markets. The patterns embedded in the price movements are revealed and shed light on the market dynamics. Financial policymakers and regulators can gain inspiration from these findings for applications in policy making, regulations design, portfolio management, risk management, and trading.
Faculty
Faculté des sciences et de médecine
Department
Département de Physique
Language
  • English
Classification
Economics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/307529
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