Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets
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...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/4680140 |
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| author | Yong Tang Jason Jie Xiong Zi-Yang Jia Yi-Cheng Zhang |
| author_facet | Yong Tang Jason Jie Xiong Zi-Yang Jia Yi-Cheng Zhang |
| author_sort | Yong Tang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d9ecba6afcd04f76977ddb9daa6fc159 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d9ecba6afcd04f76977ddb9daa6fc1592025-02-03T01:24:04ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/46801404680140Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock MarketsYong Tang0Jason Jie Xiong1Zi-Yang Jia2Yi-Cheng Zhang3Center of Cyberspace and Security, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, ChinaDepartment of Computer Information Systems and Supply Chain Management, Walker College of Business, Appalachian State University, Boone, NC 28608, USADepartment of Computer Science, Rutgers University, Piscataway, NJ 08854, USADepartment of Physics, University of Fribourg, Chemin du Musée 3, CH-1700 Fribourg, SwitzerlandPolicy 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.http://dx.doi.org/10.1155/2018/4680140 |
| spellingShingle | Yong Tang Jason Jie Xiong Zi-Yang Jia Yi-Cheng Zhang Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets Complexity |
| title | Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets |
| title_full | Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets |
| title_fullStr | Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets |
| title_full_unstemmed | Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets |
| title_short | Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets |
| title_sort | complexities in financial network topological dynamics modeling of emerging and developed stock markets |
| url | http://dx.doi.org/10.1155/2018/4680140 |
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