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Shareholding Networks and Centrality: An Application to the Italian Financial Market

In: Networks, Topology and Dynamics

Author

Listed:
  • M. D'Errico

    (Dipartimento di Metodi Quantitativi per le Scienze Economiche ed Aziendali Universita degli Studi di Milano — Bicocca)

  • R. Grassi

    (Dipartimento di Metodi Quantitativi per le Scienze Economiche ed Aziendali Universita degli Studi di Milano — Bicocca)

  • S. Stefani

    (Dipartimento di Metodi Quantitativi per le Scienze Economiche ed Aziendali Universita degli Studi di Milano — Bicocca)

  • A. Torriero

    (Finanza matematica e Econometria Universita Cattolica del Sacro Cuore di Milano)

Abstract

In this paper we studied the Shareholding Network (SN) embedded in the Italian Stock Market (MIB). We identified the central companies both in the role of transferring information flows and controlling companies. To this end we used betweenness and flow betweenness centrality measures, together with in and out degree. We tested the scale-free property on in and out degree, betweenness and flow betweenness centrality. The effect of external shocks to SN and the different extent on which companies react to them are measured relating asset volatility and betweenness.

Suggested Citation

  • M. D'Errico & R. Grassi & S. Stefani & A. Torriero, 2009. "Shareholding Networks and Centrality: An Application to the Italian Financial Market," Lecture Notes in Economics and Mathematical Systems, in: Ahmad K. Naimzada & Silvana Stefani & Anna Torriero (ed.), Networks, Topology and Dynamics, pages 215-228, Springer.
    • Handle: RePEc:spr:lnechp:978-3-540-68409-1_11
    DOI: 10.1007/978-3-540-68409-1_11
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    Citations

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    Cited by:

    1. Michel Alexandre & Kau^e Lopes de Moraes & Francisco Aparecido Rodrigues, 2021. "Risk-dependent centrality in the Brazilian stock market," Papers 2103.09059, arXiv.org.
    2. Sun, Bowen & Li, Huajiao & An, Pengli & Wang, Ze, 2020. "Dynamic energy stock selection based on shareholders’ coholding network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    3. Roy Cerqueti & Giulia Rotundo, 2023. "The weighted cross-shareholding complex network: a copula approach to concentration and control in financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(2), pages 213-232, April.
    4. Roda Jean-Marc & Kamaruddin Norfaryanti & Palhiarim Tobias Rafael, 2014. "Deciphering Corporate Governance and Environmental Commitments among Southeast Asian Transnationals: Uptake of Sustainability Certification," Working Papers 40412, CIRAD, Forest department, UPR40, revised May 2015.
    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. Anna Maria D’Arcangelis & Giulia Rotundo, 2016. "Complex Networks in Finance," Lecture Notes in Economics and Mathematical Systems, in: Pasquale Commendatore & Mariano Matilla-García & Luis M. Varela & Jose S. Cánovas (ed.), Complex Networks and Dynamics, pages 209-235, Springer.
    7. Fausto Bonacina & Marco D’Errico & Enrico Moretto & Silvana Stefani & Anna Torriero & Giovanni Zambruno, 2015. "A multiple network approach to corporate governance," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1585-1595, July.
    8. Hung-Chun Huang & Hsin-Yu Shih & Tsung-Han Ke, 2017. "Structure of a patent transaction network," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 25-45, April.
    9. Li, Jie & Ren, Da & Feng, Xu & Zhang, Yongjie, 2016. "Network of listed companies based on common shareholders and the prediction of market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 508-521.

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