Unitus DSpaceThe DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.http://http://dspace.unitus.it:802018-02-21T07:40:43Z2018-02-21T07:40:43ZOwnership and control in shareholding networksRotundo, GiuliaD'Arcangelis, Anna Mariahttp://hdl.handle.net/2067/15072011-03-25T01:30:53Z2009-12-31T23:00:00ZTitle: Ownership and control in shareholding networks
Authors: Rotundo, Giulia; D'Arcangelis, Anna Maria
Abstract: This paper aims to provide a network analysis of the relationships of shareholders in the Italian stock market for understanding the relevance of portfolio diversification in integrated ownership and firms control. The analysis combines both a complex network and an operational research approach. The former is used for statistical analyses on portfolio diversification. The latter estimates integrated ownership considering the paths on the network, and it emphasizes the difference between ownership and control. The dataset consists of nearly 300 companies traded on the Italian Stock Market. Data were retrieved through CONSOB and AIDA database, and they are adjourned at 2008. The dataset is completed with information on banks and insurance companies. Such data were retrieved through BANKSCOPE and ISIS databases.2009-12-31T23:00:00ZNetwork analysis of ownership and control structure in the Italian Stock marketRotundo, GiuliaD'Arcangelis, Anna Mariahttp://hdl.handle.net/2067/15082011-03-25T01:30:53Z2009-12-31T23:00:00ZTitle: Network analysis of ownership and control structure in the Italian Stock market
Authors: Rotundo, Giulia; D'Arcangelis, Anna Maria
Abstract: This work has two targets. First, we gather data on the board of directors of companies traded on the Italian Stock Market, and we analyze the structure of the related network. Second, we measure the overlap among the network of the board of directors and the shareholding network, and we evaluate the relevance of the board of directors on control, effective control, and cross-ownership relationships. In fact, shareholding data, that we have already analyzed in a previous work, capture a part only of the dependence structure, while the companies that are on the market since many years interact most through social means and common directors. Thus, such approach is a first step towards the merge of social interaction information into the analysis of ties of companies. Although we are aware that a complete analysis of social interaction and families would reveal extra complex interactions, we show how public available information changes the set of controller and controlled companies.
The results point out a cause of structural risk of the market that is not considered by usual econometric models for time series of returns, and it provides a basis for the development of new indicators for risk that overcome the standard approaches most based on the time series analysis of raw return time series.
Methods used in the present analysis involve statistical analyses most proper of the field of complex networks and graph flow analysis typical of operations research approach.
The dataset reports the board of directors (CONSOB database), and the shareholdings of nearly 300 companies traded on the Italian Stock Market. Data, adjourned at May 2008, were retrieved through the AIDA database, integrated by the Bureau van Dijk databases BANKSCOPE, ISIS, and cross-validated through CONSOB and MEDIOBANCA reports.2009-12-31T23:00:00ZNetwork of firms: an analysis of the relevance of integrated ownership in market concentrationRotundo, GiuliaD'Arcangelis, Anna Mariahttp://hdl.handle.net/2067/15222011-03-25T01:30:21Z2008-12-31T23:00:00ZTitle: Network of firms: an analysis of the relevance of integrated ownership in market concentration
Authors: Rotundo, Giulia; D'Arcangelis, Anna Maria
Abstract: This paper aims to provide an analysis the structure of ownership and control of firms whose
shares are traded on the Italian Stock Market. The work is relevant for adding knowledge on the
diversification of risk and ultimately to work for the development of risk indicators beyond the
standard approaches most based on the time series analysis of raw price time series. The dataset
reports the shareholdings of 247 companies traded on the Italian stock market. Data, adjourned at
May 2008, were retrieved through the AIDA database, integrated by the Bureau van Dijk
databases BANKSCOPE, ISIS, and cross-validated through CONSOB and MEDIOBANCA
reports. Therefore, this dataset allows to consider a sampling larger than the one examined in [2],
even considering the difference in the companies traded in the Italian stock market due to the
different sampling date. Fig. 1 shows the most connected nodes of the shareholding network.
We are most interested in understanding the role of portfolio diversification and portfolio size in
the structure of ownership and control.
Methods used in the present analysis involve statistical analyses most proper of the field of
complex networks [3] and graph flow analysis typical of operations research approach [1, 4].
We start our analysis building a network from data. Each company corresponds to a node and a
link from node i to node j exists if i owns shares of j. Therefore, we obtain a directed graph and
the direction of our links is the opposite of the ones of [2], but the same used in [4].
Therefore, in our network construction, the number of links exiting from a node, kout, measures
portfolio diversification. The number of links entering in a node, kin, shows the number of
shareholders, but this data is biased due to the sample, like it happens in [2].
We are most interested in outlining the difference between ownership, control, and the overlap
between ownership and control paths and portfolio diversification. Portfolio diversification is
measured through mere statistical analysis, assortativity, and hierarchical paths estimate, in
accord with the measure introduced in [5]. We both estimate the probability distribution and the
relationship between kout of network nodes. We remark the absence of power laws, although a
comparison with the results of [2] allows to detect the tendency to lower the diversification.
We consider also the correlation of kout between different nodes. Having detected a low positive
degree of assortativity (0.17), we deepen the analysis by estimating the percentage of
hierarchical paths. Two nodes i and j are in a hierarchical path if an “up” path exists from node i
through nodes with higher kout, followed by a “down” path where nodes on the path have a
decreasing kout. Therefore, a hierarchical path exists if node i is in the portfolio of a larger
investor, in which also the smaller j is investing.
Capitalization is introduced and the analysis is carried on the portfolio size as well. This allows
to measure the overlap between portfolio diversification and capitalization, and to answer to
questions on the possibility to diversify portfolios for companies having a smaller capitalization.
Given the distribution of nodes, we determine its distance form the maximum (minimum)
hierarchical ones, and provide ranges for possible scenarios.
We compare this data with the results of the analysis of ownership/control, based on techniques
of operational research [1, 4]. The method shown in [4] deals with directed acyclic graph (DAG),
whilst [1] considers connected components. The entire network becomes DAG only whether
links corresponding to more 10% share ownerships are considered. Hence, cycles cannot be
eliminated without cutting relevant information. The results emphasize that companies traded on
the Italian stock market most use direct control.2008-12-31T23:00:00Z