The layered structure of company share networks (original) (raw)

A multiple network approach to corporate governance

2014

In this work, we consider Corporate Governance (CG) ties among companies from a multiple network perspective. Such a structure naturally arises from the close interrelation between the Shareholding Network (SH) and the Board of Directors network (BD). In order to capture the simultaneous effects of both networks on CG, we propose to model the CG multiple network structure via tensor analysis. In particular, we consider the TOPHITS model, based on the PARAFAC tensor decomposition, to show that tensor techniques can be successfully applied in this context. After providing some empirical results from the Italian financial market in the univariate case, we will then show that a tensor -based multiple network approach can reveal important information.

Control and voting power in corporate networks: Concepts and computational aspects

European Journal of Operational Research, 2007

ABSTRACT This paper proposes to rely on power indices to measure the amount of control held by individual shareholders in corporate networks. The value of the indices is determined by a complex voting game viewed as the composition of interlocked weighted majority games; the compound game reflects the structure of shareholdings. The paper describes an integrated algorithmic approach which allows to deal efficiently with the complexity of computing power indices in shareholding networks, irrespective of their size or structure. In particular, the approach explicitly accounts for the presence of float and of cyclic shareholding relationships. It has been successfully applied to the analysis of real-world financial networks.

Rebuilding the Great Pyramids: A Method for Identifying Control Relations in Complex Ownership Structures

SSRN Electronic Journal, 2000

Identifying the corporate controller (controlling shareholder, ultimate owner) is an essential prerequisite for any debate on the corporate governance of a specific firm and of entire markets. This paper aims to provide a comprehensive, precise and economically sound method for identifying control relations on the corporate level and especially in complex ownership structures. We apply weighted voting games literature as a theoretical framework for our analysis and use the Shapley-Shubik and the Banzhaf power indices to determine control rights. The core element of the proposed method, distinguishing our study from others, in solving the puzzle of corporate control, is the simultaneous analysis of both the specific ownership map within the corporation and the corporate network in which the firm is embedded. We implemented our algorithm into a Java computer program and tested it on a real-world data set of corporate ownership in the Israeli market. The direct product of the analysis of these data is a comprehensive map of control relations at every time point. We find that the corporate control relations identified by our method are richer and more accurate than those provided by different official sources.

Analysis of ownership network of European companies using gravity models

Applied Network Science

Social network analysis is increasingly applied to modeling regional relationships. However, in this scenario, we cannot ignore the geographical economic and technological nature of the relationships. In this study, the tools of social network analysis and the gravity model are combined. Our study is based on the Amadeus database of European organizations, which includes 24 million companies. The ownership of parent subsidiaries was modeled using economic, technological, and geographic factors. Ownership was aggregated to the NUTS 3 regional level, to which average corporate profitability indicators, the GDP per capita characterizing the economic environment, and the number of patents, which is a proxy of the technological environment, were assigned to NUTS 3 regions. The formation of the ownership network between 2010 and 2018 was characterized using this dataset. As the proposed model accurately describes the formation of ownership relationships marked with edges, it is possible t...

A Snapshot of the Ownership Network of the Budapest Stock Exchange

In this study, I use the toolkit of network research to explore the network of ownership relations of entities present on the Budapest Stock Exchange as issuers in 2020, applying static methods and exponential random graph modelling (ERGM) analysis. In the snapshot typology and simulation-based capture of the network, not only the network of relations between issuers present on the stock market is analysed, but also the ownership relations of companies connected to the network but not listed on the stock market; thus, the study addresses the ownership network associated with the stock exchange as a whole. The research results provide us with an accurate answer about the morphological characteristics of the network, the network factors determining centrality, the hierarchy of the network, and the evolution of the network with the help of simulations. The study may allow us to obtain a clearer picture of the interlinkages and clusters of companies listed on the stock market, which can be used as a basis for subsequent longitudinal analyses.

Topological and Dynamical Properties of the Network of Shareholders in S&P 500 Companies Based on Graph Databases

JOURNAL OF INTERNATIONAL MONEY, BANKING AND FINANCE

The interesting properties of scale-free and small-world networks recently observed have triggered the attention of the research community to the study of real growing complex networks. In scale-free networks, most vertices are sparsely connected, while a few vertices are intensively connected to many others, indicating a “preferential linking” during growing. In small-world networks, the average length of the shortest path between two randomly chosen nodes is small. In this paper, we study the topological and dynamical properties of the network of shareholders (NOS) in 11593 different companies. Based on Graph Databases, we calculate all the well-known in the literature topological and dynamical properties of a network along with centrality measures of nodes of NOS, which quantify the role that a node plays in the overall structure of NOS. We prove that NOS is both a scale-free and smallworld network. An understanding of NOS helps in predicting the emergence of important new phenom...

Corporate Governance Analysis and Social Networks: A Case Study in Greek Firms

2014

In this paper, we use a set of publicly available date regarding Greek Firms in order to investigate probable connections between the structure of their Boards of Directors and its possible linkage to the creation of the recent financial crisis in Greece or possible corruption existence. This study is developed in two parts. In the first part we create and analyze two derived social networks, using well known and robust metrics from the theory of Social Network Analysis. In the second part we examine any existing relation between corporate ownership structure and the information content of announced earnings.The empirical results of this study are generally consistent with the above arguments.

TOPOLOGICAL AND DYNAMICAL PROPERTIES OF THE NETWORK OF SHAREHOLDERS IN S&P 500 COMPANIES BASED ON GRAPH DATABASES

2022

The interesting properties of scale-free and small-world networks recently observed have triggered the attention of the research community to the study of real growing complex networks. In scale-free networks, most vertices are sparsely connected, while a few vertices are intensively connected to many others, indicating a "preferential linking" during growing. In small-world networks, the average length of the shortest path between two randomly chosen nodes is small. In this paper, we study the topological and dynamical properties of the network of shareholders (NOS) in 11593 different companies. Based on Graph Databases, we calculate all the well-known in the literature topological and dynamical properties of a network along with centrality measures of nodes of NOS, which quantify the role that a node plays in the overall structure of NOS. We prove that NOS is both a scale-free and smallworld network. An understanding of NOS helps in predicting the emergence of important new phenomena affecting portfolio management in general. Also, this work reveals the fact that graph databases could serve as an efficient tool for analyzing such network models for stock markets. To the best of the authors' knowledge, this is the first study calculating all the well-known in the literature topological and dynamical properties for Market Investments Networks, that is based on graph databases.

Weaving Enterprise Knowledge Graphs: The Case of Company Ownership Graphs

2020

Motivated by our experience in building the Enterprise Knowledge Graph of Italian companies for the Central Bank of Italy, in this paper we present an in-depth case analysis of company ownership graphs, graphs having company ownership as a central concept. In particular, we study and introduce three industrially relevant problems related to such graphs: company control, asset eligibility and detection of personal links. We formally characterize the problems and present Vada-Link, a framework based on state-of-the-art approaches for knowledge representation and reasoning. With our methodology and system, we solve the problems at hand in a scalable, model-independent and generalizable way.We illustrate the favourable architectural properties ofVadaLink and give experimental evaluation of the approach.