Systemic importance of financial institutions: A complex network perspective

Xin, Yang; Wen, Shigang; Zhao, Xian; Huang, Chuangxia

doi:10.1016/j.physa.2019.123448

Cited by 15 publications

(5 citation statements)

References 51 publications

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“…Complex networks have proven to be a very powerful approach to characterize and analyze a broad array of different complex systems [3][4][5][6][7], such as human migration [8][9][10], biological mathematics [11,12], technological [13][14][15][16][17] and finance systems [18][19][20][21][22][23][24]. These highly inter-coupled systems have been the focus of a great number of researches, which have investigated influential nodes of the systems.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Global Remittance Based on Complex Networks

Wen

et al. 2020

Front. Phys.

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Remittance, one money flow between immigrants and their relatives, is a major source of foreign exchange revenue for economies. Consisting of economies linked by the money flows, global remittance constitutes a network. In this paper, we use bilateral remittances of 210 economies for the time period 2010-2016 to construct a global remittance network (GRN) and then investigate the network's structural properties. We study the degree distribution of the network and find that it is of heterogeneity. Analyses of centrality measures reveal that some key economies, such as the United States, France, India and China, are always ranked the highest. We also detect 6 communities in the network, where economies in the same regional economy cooperative organizations tend to be classified in the same community. Intra-community flows account for 66.07% of total remittances, indicating that economies present the characteristic of regionalization. In addition, the results of the topological stability test show that GRN is fragile to node removal, particular the selective removal based on betweenness centrality.

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Section: Introductionmentioning

confidence: 99%

Analysis of Global Remittance Based on Complex Networks

Wen

et al. 2020

Front. Phys.

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“…Due to the lack of available data, while the quantitative method has become a trend in economy related issues [39][40][41][42][43][44][45], most of the researches belong to qualitative analysis in Convention and Exhibition industry area, and we try to utilize the following spatial econometric model to investigate the exact relationship between financial flexibility and investment. e first step of studying the existence of the spatial spillover effect is correctly setting the spatial econometric model.…”

Section: Benchmark Model Settings and Descriptionsmentioning

confidence: 99%

Spatial Spillover Effect of Financial Flexibility on Investment in China’s Convention and Exhibition Listed Companies

Liu

Zhang

et al. 2020

Mathematical Problems in Engineering

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Financial flexibility is an important research issue in corporate finance. This paper utilizes the Spatial Durbin Model (SDM) to analyze the impact of financial flexibility on the investment of Convention and Exhibition companies listed on the New Third Board from 2014 to 2016. The empirical results show the following. Firstly, the greater the financial flexibility, the more investment the firm will make. Secondly, the enhancement in financial flexibility would lead to an increase in investment of companies in the Convention and Exhibition industry in the local provinces, indicating that the financial flexibility has a significant positive intraregional spatial spillover effect on investment. On the other hand, financial flexibility has spatial spillover effects, and its rise will reduce the investment in other provinces, which could be explained by the competition effect between enterprises. Overall, we have further elucidated the role of different levels of financial flexibility on the investment of the Convention and Exhibition listed enterprises from the spatial dimension, thereby enriching the existing research on corporate financial flexibility and corporate value to some certain extent.

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“…An example is the collapse of Lehman Brothers Holding, which eventually led to the 2008 global financial crisis. One systematic way to analyze the significance and impacts of companies is to use complex networks based on Interaction Graphs (IGs) (Yang et al, 2020). In this method, the graph vertices represent the stock exchange companies that are connected by weighted edges (corresponding to the extent to which they relate to each other).…”

Section: Introductionmentioning

confidence: 99%

Investigating the Importance of Different Companies of Tehran Stock Exchange using Lower Tail Dependency based Interaction Network

Osoolian

Esfidvajani

Ramezani

2023

IJFIFSA

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Examining the importance and influence of financial market companies is one of the main issues in the field of financial management because sometimes the collapse of a stock exchange company can affect an entire financial market. One systematic way to analyze the significance and impacts of companies is to use complex networks based on Interaction Graphs (IGs). There are different methods for quantifying the edge weight in an IG. In this method, the graph vertices represent the stock exchange companies that are connected by weighted edges (corresponding to the extent to which they relate to each other). In this paper, using the GARCH model (1,1) and the Clayton copula, we obtained the lower tail dependence interaction network of the first 52 companies of the Tehran Stock Exchange in terms of average market value, between June 2017 and October 2020. Then, based on the minimum spanning tree of the interaction network, we divided the companies into different communities. Using this classification, it was observed that the companies of the first group (Food Industry) and the second group (Oil Refinery) have the greatest impact on other companies. We also calculated the central indexes of the minimum spanning tree for each company. According to the results, the companies of the third group (Steel) have the highest average in the central indicators.

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Systemic importance of financial institutions: A complex network perspective

Cited by 15 publications

References 51 publications

Analysis of Global Remittance Based on Complex Networks

Analysis of Global Remittance Based on Complex Networks

Spatial Spillover Effect of Financial Flexibility on Investment in China’s Convention and Exhibition Listed Companies

Investigating the Importance of Different Companies of Tehran Stock Exchange using Lower Tail Dependency based Interaction Network

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