Controlling systemic risk - network structures that minimize it and node properties to calculate it (CROSBI ID 278729)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Krause, Sebastian M. ; Štefančić, Hrvoje ; Zlatić, Vinko ; Caldarelli, Guido
engleski
Controlling systemic risk - network structures that minimize it and node properties to calculate it
Evaluation of systemic risk in networks of financial institutions in general requires information of inter-institution financial exposures. In the framework of Debt Rank algorithm, we introduce an approximate method of systemic risk evaluation which requires only node properties, such as total assets and liabilities, as inputs. We demonstrate that this approximation captures a large portion of systemic risk measured by Debt Rank. Furthermore, using Monte Carlo simulations, we investigate network structures that can amplify systemic risk. Indeed, while no topology in general sense is {;\em a priori}; more stable if the market is liquid [1], a larger complexity is detrimental for the overall stability [2]. Here we find that the measure of scalar assortativity correlates well with level of systemic risk. In particular, network structures with high systemic risk are scalar assortative, meaning that risky banks are mostly exposed to other risky banks. Network structures with low systemic risk are scalar disassortative, with interactions of risky banks with stable banks.
risk management ; theoretical economics ; physics and society
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Podaci o izdanju
103 (4)
2021.
042304
15
objavljeno
2470-0045
2470-0053
10.1103/PhysRevE.103.042304
Povezanost rada
Ekonomija, Fizika, Interdisciplinarne prirodne znanosti