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Global Banking on the Financial Network Modelling: Sectorial Analysis

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Abstract

This article is particularly concentrated on measuring systemic risk based on network topology of bilateral exposures and obligations specifically for the sectoral level of global banking systems in 2010. Financial network models based on financial exposures are models that aim to depict causal chains of exposures and obligations of counterparties rather than rely solely on statistical correlations on market price-based data for financial institutions. Our starting point is the bilateral claims of the ultimate risk of the main institutional sectors that include banks, non-bank private sectors and non-allocated sectors of the 10 reporting countries that consist of Belgium, France, Germany, Italy, Japan, Spain, Switzerland, Turkey, the United Kingdom and the United States of America. The other non-reporting countries will be merged into one group. The results show that banking systems in countries such as the United States and the United Kingdom in particular are making vast amounts of foreign investments, implying that they constitute a central hub in the core. The results in the contagion effect show that all of the other countries are collapsed after a shock from a core country such as the United Kingdom in both rates of loss given defaults of 100 and 60 %.

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Notes

  1. We adjust the amounts to be in 2005 US dollars by using the U.S. Department of Labor Bureau of Labor Statistics Consumer Price Index (CPI). We take the average of annualised monthly index values rather than using the year-end index values in order to capture the inherent structure of flows.

  2. Newman (2010, p. 237) suggests that the majority of the social, information, technological and biological networks are scale-free networks such that the exponent \(\alpha \) ranges between 2 and 3. For instance, the exponent for networks such as the World Wide Web, film actors and telephone calls are 2.5, 2.3 and 2.1, respectively.

  3. In this research, the condition that \(k_{\min }\) is greater than \(3^{\prime \prime }\) is satisfied for all networks during 2010.

  4. For the proof, pls. see pp. 346 and 347 of Newman (2010).

  5. We follow the same method of Degryse et al. (2010) for the calculation of a banking system aggregate equity. Additionally, we prefer to use consolidated accounting statements if they are available. On the other hand, we prefer to use accounting statements based on International Financial Reporting Standards (IFRS).

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  1. Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Fathin Faizah Said

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Said, F.F. Global Banking on the Financial Network Modelling: Sectorial Analysis. Comput Econ 49, 227–253 (2017). https://doi.org/10.1007/s10614-015-9556-x

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