Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks
The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/8/1240 |
| _version_ | 1797584832387088384 |
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| author | Wenyan Peng Tingting Chen Bo Zheng Xiongfei Jiang |
| author_facet | Wenyan Peng Tingting Chen Bo Zheng Xiongfei Jiang |
| author_sort | Wenyan Peng |
| collection | DOAJ |
| description | The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies. |
| first_indexed | 2024-03-10T23:57:20Z |
| format | Article |
| id | doaj.art-7149e468e5ba4e5da1b9a0a3d7066850 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T23:57:20Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-7149e468e5ba4e5da1b9a0a3d70668502023-11-19T01:00:38ZengMDPI AGEntropy1099-43002023-08-01258124010.3390/e25081240Spreading Dynamics of Capital Flow Transfer in Complex Financial NetworksWenyan Peng0Tingting Chen1Bo Zheng2Xiongfei Jiang3Department of Physics, Zhejiang University, Hangzhou 310018, ChinaDepartment of Finance, Zhejiang University of Finance and Economics, Hangzhou 310018, ChinaDepartment of Physics, Zhejiang University, Hangzhou 310018, ChinaCollege of Finance and Information, Ningbo University of Finance and Economics, Ningbo 315175, ChinaThe financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies.https://www.mdpi.com/1099-4300/25/8/1240complex networksfinancial systemscapital flowtransfer entropyeconophysics |
| spellingShingle | Wenyan Peng Tingting Chen Bo Zheng Xiongfei Jiang Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks Entropy complex networks financial systems capital flow transfer entropy econophysics |
| title | Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks |
| title_full | Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks |
| title_fullStr | Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks |
| title_full_unstemmed | Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks |
| title_short | Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks |
| title_sort | spreading dynamics of capital flow transfer in complex financial networks |
| topic | complex networks financial systems capital flow transfer entropy econophysics |
| url | https://www.mdpi.com/1099-4300/25/8/1240 |
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