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Communities in Italian corporate networks

Author Info

  • 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).

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File URL: http://www.sciencedirect.com/science/article/pii/S0378437110005674
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Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 389 (2010)
Issue (Month): 22 ()
Pages: 5247-5258

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Handle: RePEc:eee:phsmap:v:389:y:2010:i:22:p:5247-5258
Contact details of provider: Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Keywords: Networks; Communities; Modularity; Board network; Ownership network;

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Cited by:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. Stefania Vitali & Stefano Battiston, 2013. "The Community Structure of the Global Corporate Network," Papers 1301.2363, arXiv.org.
  12. 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.
  13. 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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