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The study of the financial market and its behavior has grown in importance after the 2007-2009 worldwide financial crisis, and policymaker financial institutions have called the attention of the academy on mathematic and computation research axis to handle the problem of systemic risk and contagion propagation. As a consequence, social network analysis techniques have been used to study financial systems, in particular the interbank market, based on banks’ interactions or bilateral exposures (money lending/borrowing) during usually short time periods. The interbank market is a network modeled as a directed graph, where nodes are banks and edges are bilateral exposures. The academy produced a lot of literature on financial networks as a response to this challenge, however, the graphical tools available for network analysis are not specifically oriented to the interbank market. In this sense, the goal of this work is to study indicators used in the Gephi graphic open source tool for computation, visualization and manipulation of complex networks, to provide guidelines on how they can be used and visualized in the interbank market context. Some of these indicators, such as centrality measures, have been found useful to measure the importance of banks and the impact of their bilateral transactions. We hope that our results can be useful to financial specialists and economists to make full profit of a computational graphic tool to analyze the interbank market instability to prevent possible shocks. On theses bases, a computational graphic tool adapted to the interbank market analysis will be designed soon. |
