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Systemic risk in a macro-multiplex network
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AI
DOI：10.1007/s00500-023-09460-7.png)
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Abstract
En 中文
Network models of the financial system have become increasingly popular since the financial crisis of 2007-2009 due to their capabilities for analyzing complex relational data. Nowadays, most of these models have multiple layers in order to account for the many markets of the financial system in which agents operate simultaneously. However, these models are usually restricted to simulated data due to the lack of public information about the positions of financial institutions. Despite their importance, this information is even more difficult to get for institutions that are not banks. In this paper, we propose a model that employs macrofinancial data of the aggregated financial claims between countries ordered in four layers: banks, financial institutions which are not banks, official institutions and non-financial corporations. The two principal objectives(i) To analyze the differences in systemic risk measurement when considering a monoplex or a multiplex network with real financial data, and (ii) To measure how different are the capital requirements between banks and the rest of institutions to maintain financial stability. After applying the DebtRank algorithm, the results show that there are considerable differences between the monoplex and the multiplex setup, and that the capital requirements for financial institutions are only slightly lower than those for banks.
Keywords:
Multiplex financial networks
Systemic risk
Capital requirements
Shadow banking