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Main Author: Ugwu, Sunday Akukodi
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.08071
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author Ugwu, Sunday Akukodi
author_facet Ugwu, Sunday Akukodi
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2402_08071
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Contagion on Financial Networks: An Introduction
Ugwu, Sunday Akukodi
Statistical Finance
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.
title Contagion on Financial Networks: An Introduction
topic Statistical Finance
url https://arxiv.org/abs/2402.08071