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Communities in Italian corporate networks

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  • Piccardi, Carlo
  • Calatroni, Lisa
  • Bertoni, Fabio

Abstract

The community structure of two real-world financial networks, namely the board network and the ownership network of the firms of the Italian Stock Exchange, is analyzed by means of the maximum modularity approach. The main result is that both networks exhibit a strong community structure and, moreover, that the two structures overlap significantly. This is due to a number of reasons, including the existence of pyramidal groups and directors serving in several boards. Overall, this means that the “small world” of listed companies is actually split into well identifiable “continents” (i.e., the communities).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:22:p:5247-5258
    DOI: 10.1016/j.physa.2010.06.038
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    Cited by:

    1. Leonardo Bargigli & Renato Giannetti, 2015. "The Italian Corporate System: SOEs, Private Firms and Institutions in a Network Perspective (1952-1983)," Working Papers - Economics wp2015_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    2. Francesca Pallotti & Alessandro Lomi & Daniele Mascia, 2013. "From network ties to network structures: Exponential Random Graph Models of interorganizational relations," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1665-1685, April.
    3. 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.
    4. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    5. Shen, Yi, 2014. "The similarity of weights on edges and discovering of community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 560-570.
    6. Sun, Xiao-Qian & Shen, Hua-Wei & Cheng, Xue-Qi & Zhang, Yuqing, 2017. "Detecting anomalous traders using multi-slice network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 1-9.
    7. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    8. Wu, Jianshe & Li, Xiaoxiao & Jiao, Licheng & Wang, Xiaohua & Sun, Bo, 2013. "Minimum spanning trees for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2265-2277.
    9. Drago, Carlo, 2015. "Exploring the Community Structure of Complex Networks," MPRA Paper 81024, University Library of Munich, Germany.
    10. Zhong, Tao & Peng, Qinke & Wang, Xiao & Zhang, Jing, 2016. "Novel indexes based on network structure to indicate financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 583-594.
    11. Stefania Vitali & Stefano Battiston, 2014. "The Community Structure of the Global Corporate Network," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-13, August.
    12. Bargigli, L. & Giannetti, R., 2018. "The Italian corporate system in a network perspective (1952–1983)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 367-379.
    13. Lucia Bellenzier & Rosanna Grassi, 2014. "Interlocking directorates in Italy: persistent links in network dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 183-202, October.
    14. Sankowska, Anna & Siudak, Dariusz, 2016. "The small world phenomenon and assortative mixing in Polish corporate board and director networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 309-315.
    15. Sun, Xiao-Qian & Cheng, Xue-Qi & Shen, Hua-Wei & Wang, Zhao-Yang, 2011. "Distinguishing manipulated stocks via trading network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3427-3434.
    16. 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.
    17. 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.
    18. Polovnikov, Kirill & Kazakov, Vlad & Syntulsky, Sergey, 2020. "Core–periphery organization of the cryptocurrency market inferred by the modularity operator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    19. Song, Xiao & Shi, Wen & Ma, Yaofei & Yang, Chen, 2015. "Impact of informal networks on opinion dynamics in hierarchically formal organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 916-924.
    20. Carlo Piccardi, 2011. "Finding and Testing Network Communities by Lumped Markov Chains," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
    21. Drago, Carlo, 2015. "Exploring the Community Structure of Complex Networks," MPRA Paper 81024, University Library of Munich, Germany.
    22. Xiao-Qian Sun & Xue-Qi Cheng & Hua-Wei Shen & Zhao-Yang Wang, 2011. "Distinguishing manipulated stocks via trading network analysis," Papers 1110.2260, arXiv.org.

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