RETRACTED ARTICLE: Measuring the systemic importance of Chinese banks based on risk interactions
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Measuring the systemic importance of Chinese banks based on risk interactions Abdelkader Derbali1,2 · Lamia Jamel3 · Shan Wu4 Received: 20 June 2019 / Accepted: 7 February 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Systemic importance of a financial institution is usually measured by the impact on the banking system conditional on the insolvency of this bank and solvency of other banks. However, in reality banks encounter diverse kinds of shocks simultaneously. Therefore, the conditional results give biased estimates of financial institution systemic importance when interactions of various risks are ignored. A number of researchers propose the Shapley value method to deal with risk connections, but it suffers heavy computational cost. In our paper, we propose an analysis of variance-like decomposition method to measure systemic importance of banks in more complicated and realistic environments. This method takes both interactions and individual effects of multiple shocks into reflection and provides a more precise estimation of systemic importance. We find the proposed methodology fits well in the network models. In the numerical example, we provide a discussion of our methodology and the Shapley value method, showing the advantage of the method: Shapley value method needs running of 2n subsystems, while our method needs only n + 1 model runs. At last, the proposed methodology is applied to the Chinese banking system with 16 listed banks. Our empirical findings confirm that interactions of different shocks play a significant role in systemic importance of a bank, and thus, the total impact considering interactions should be adopted. Keywords Systemic risk · Interbank network · Risk interaction · Systemically important bank · Analysis of variance-like decomposition method JEL Classification D53 · E02 · E44 · G21 · G32
1 Introduction In the background of quick integration of the global financial market, financial institutions have become more connected to each other via a sophisticated financial system
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of multilateral exposures. As a result, bankruptcy of one institution may generate an amplified effect on the whole banking system, which is termed as systemic risk. Systemic risk in the financial institutions system has received increasing attention from researchers, regulators and supranational agencies (Akhter and Daly 2017; Demange 2016; Elsinger et al. 2006; Giordana 2015; Glasserman and Young 2015; Derbali et al. 2015ab; Pourkhanali et al. 2016; Ramsay and Sarlin 2016; Tarashev et al. 2016; Derbali 2016; Derbali and Hallara 2016a, b; Derbali 2017a, b). One of the vital issues is to identify systemically important financial institutions, especially banks, which have the majority contribution to the banking system or have more systemic risk than others banks. In general, two strands of methodologies are adopted when studying systemic risk. The first methodology focuses on capturing the
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