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Contagion on Financial Networks: An Introduction

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  • Sunday Akukodi Ugwu

Abstract

This mini-project models propagation of shocks, in time point, through links in connected banks. In particular, financial network of 100 banks out of which 15 are shocked to default (that is, 85.00% of the banks are solvent) is modelled using Erdos and Renyi network -- directed, weighted and randomly generated network. Shocking some banks in a financial network implies removing their assets and redistributing their liabilities to other connected ones in the network. The banks are nodes and two ranges of probability values determine tendency of having a link between a pair of banks. Our major finding shows that the ranges of probability values and banks' percentage solvency have positive correlation.

Suggested Citation

  • Sunday Akukodi Ugwu, 2024. "Contagion on Financial Networks: An Introduction," Papers 2402.08071, arXiv.org, revised Feb 2024.
    • Handle: RePEc:arx:papers:2402.08071
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    References listed on IDEAS

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    1. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    2. Hamed Amini & Rama Cont & Andreea Minca, 2016. "Resilience To Contagion In Financial Networks," Mathematical Finance, Wiley Blackwell, vol. 26(2), pages 329-365, April.
    3. Abduraimova, Kumushoy & Nahai-Williamson, Paul, 2021. "Solvency distress contagion risk: network structure, bank heterogeneity and systemic resilience," Bank of England working papers 909, Bank of England.
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