The scale-free topology of market investments

Garlaschelli, Diego; Battiston, Stefano; Castri, Maurizio; Servedio, Vito D. P.; Caldarelli, Guido

doi:10.1016/j.physa.2004.11.040

Cited by 190 publications

(145 citation statements)

References 17 publications

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“…Interfirm networks have been investigated by several papers [1,2,4,5]. In particular, shareholding networks have been examined for those firms listed in the United States, Japan, and Italy [2,5], to find that these networks have scale-free characteristics, and that indegree exhibits power-law distributions.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, shareholding networks have been examined for those firms listed in the United States, Japan, and Italy [2,5], to find that these networks have scale-free characteristics, and that indegree exhibits power-law distributions. But these existing studies have only looked at a small subset of firms, typically listed firms or firms in a specific industry or region.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Do larger firms have more interfirm relationships?

Saito

Watanabe

Iwamura

2007

Physica A: Statistical Mechanics and its Applications

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In this study, we investigate interfirm networks by employing a unique dataset containing information on more than 800,000 Japanese firms, about half of all corporate firms currently operating in Japan. First, we find that the number of relationships, measured by the indegree, has a fat tail distribution, implying that there exist "hub" firms with a large number of relationships. Moreover, the indegree distribution for those hub firms also exhibits a fat tail, suggesting the existence of "super-hub" firms. Second, we find that larger firms tend to have more counterparts, but the relationship between firms' size and the number of their counterparts is not necessarily proportional; firms that already have a large number of counterparts tend to grow without proportionately expanding it.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Do larger firms have more interfirm relationships?

Saito

Watanabe

Iwamura

2007

Physica A: Statistical Mechanics and its Applications

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show abstract

“…The exponent γ depends on the year, as summarized in Table. 1. It has also been reported that the degree distributions of shareholding networks for companies listed on the Italian stock market (Milano Italia Borsa; MIB), the New York Stock Exchange (NYSE), and the National Association of Security Dealers Automated Quotations (NASDAQ) each follow the power law distribution [5] tial part of the distribution is mainly constructed from financial institutions. On the other hand, almost all of the power law part of the distribution is constructed from non-financial institutions.…”

Section: Change Of Outgoing Degree Distributionmentioning

confidence: 99%

“…This development also holds true in the field of econophysics. Such studies have investigated business networks [9], shareholding networks [10,11,12,5], world trade networks [6,7], and corporate board networks [2,4].…”

Section: Introductionmentioning

confidence: 99%

Change of ownership networks in Japan

Souma

Fujiwara

Aoyama

Practical Fruits of Econophysics

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Summary. As complex networks in economics, we consider Japanese shareholding networks as they existed in 1985, 1990, 1995, 2000, 2002, and 2003. In this study, we use as data lists of shareholders for companies listed on the stock market or on the over-the-counter market. The lengths of the shareholder lists vary with the companies, and we use lists for the top 20 shareholders. We represent these shareholding networks as a directed graph by drawing arrows from shareholders to stock corporations. Consequently, the distribution of incoming edges has an upper bound, while that of outgoing edges has no bound. This representation shows that for all years the distributions of outgoing degrees can be well explained by the power law function with an exponential tail. The exponent depends on the year and the country, while the power law shape is maintained universally. We show that the exponent strongly correlates with the long-term shareholding rate and the cross-shareholding rate.

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“…[9] for shareholding networks in MIB, NYSE, and NAS-DAQ). In this study we use data which is published by TOYO KEIZAI INC.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Economic Networks

Souma¹,

Fujiwara²,

Aoyama

Lecture Notes in Economics and Mathematical Systems

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Summary. The Japanese shareholding network at the end of March 2002 is studied. To understand the characteristics of this network intuitively, we visualize it as a directed graph and an adjacency matrix. Especially detailed features of networks concerned with the automobile industry sector are discussed by using the visualized networks. The shareholding network is also considered as an undirected graph, because many quantities characterizing networks are defined for undirected cases. For this undirected shareholding network, we show that a degree distribution is well fitted by a power law function with an exponential tail. The exponent in the power law range is γ = 1.8. We also show that the spectrum of this network follows asymptotically the power law distribution with the exponent δ = 2.6. By comparison with γ and δ, we find a scaling relation δ = 2γ − 1. The reason why this relation holds is attributed to the local tree-like structure of networks. To clarify this structure, the correlation between degrees and clustering coefficients is considered. We show that this correlation is negative and fitted by the power law function with the exponent α = 1.1. This guarantees the local tree-like structure of the network and suggests the existence of a hierarchical structure. We also show that the degree correlation is negative and follows the power law function with the exponent ν = 0.8. This indicates a degree-nonassortative network, in which hubs are not directly connected with each other. To understand these features of the network from the viewpoint of a company's growth, we consider the correlation between the degree and the company's total assets and age. It is clarified that the degree and the company's total assets correlate strongly, but the degree and the company's age have no correlation.

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The scale-free topology of market investments

Cited by 190 publications

References 17 publications

Do larger firms have more interfirm relationships?

Do larger firms have more interfirm relationships?

Change of ownership networks in Japan

Heterogeneous Economic Networks

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