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Inner structure of capital control networks

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  • Battiston, Stefano

Abstract

We study the topological structure of the network of shareholding relationships in the Italian stock market (MIB) and in two US stock markets (NYSE and NASDAQ). The portfolio diversification and the wealth invested on the market by economical agents have been shown in our previous work to have all a power law behavior. However, a further investigation shows that the inner structure of the capital control network are not at all the same across markets. The shareholding network is a weighted graph, therefore we introduce two quantities analogous to in-degree and out-degree for weighted graphs which measure, respectively: the number of effective shareholders of a stock and the number of companies effectively controlled by a single holder. Combining the information carried by the distributions of these two quantities we are able to extract the backbone of each market and we find that while the MIB splits into several separated groups of interest, the US markets is characterized by very large holders sharing control on overlapping subsets of stocks. This method seems promising for the analysis of the topology of capital control networks in general and not only in the stock market.

Suggested Citation

  • Battiston, Stefano, 2004. "Inner structure of capital control networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 107-112.
    • Handle: RePEc:eee:phsmap:v:338:y:2004:i:1:p:107-112
    DOI: 10.1016/j.physa.2004.02.031
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    Citations

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    Cited by:

    1. Tembo Nakamoto & Abhijit Chakraborty & Yuichi Ikeda, 2019. "Identification of Key Companies for International Profit Shifting in the Global Ownership Network," Papers 1904.12397, arXiv.org.
    2. Drago, Carlo & Ricciuti, Roberto, 2017. "Communities detection as a tool to assess a reform of the Italian interlocking directorship network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 91-104.
    3. S. Battiston & M. Catanzaro, 2004. "Statistical properties of corporate board and director networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 345-352, March.
    4. Hossein Dastkhan & Naser Shams Gharneh, 2019. "Simulation of Contagion in the Stock Markets Using Cross-Shareholding Networks: A Case from an Emerging Market," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1071-1101, March.
    5. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    6. Abreu, Mariana Piaia & Grassi, Rosanna & Del-Vecchio, Renata R., 2019. "Structure of control in financial networks: An application to the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 302-314.
    7. Carlo Drago & Roberto Ricciuti, 2019. "Bootstrapping the Gini Index of the Network Degree: An Application for Italian Corporate Governance," Working Papers 05/2019, University of Verona, Department of Economics.
    8. Hossein Dastkhan & Naser Shams Gharneh, 2016. "Determination of Systemically Important Companies with Cross-Shareholding Network Analysis: A Case Study from an Emerging Market," IJFS, MDPI, vol. 4(3), pages 1-17, June.

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