Reconstructing and Stress Testing Credit Networks

46 Pages Posted: 5 Nov 2020

See all articles by Amanah Ramadiah

Amanah Ramadiah

University College London - Financial Computing and Analytics Group, Department of Computer Science

Fabio Caccioli

University College London

Daniel Fricke

Deutsche Bundesbank

Multiple version iconThere are 2 versions of this paper

Date Written: September, 2018

Abstract

Financial networks are an important source of systemic risk, but often only partial network information is available. In this paper, we use data on bank-firm credit relationships in Japan and conduct a horse race between different network reconstruction methods in terms of their ability to reproduce the actual credit networks. We then compare the different reconstruction methods in terms of their implied systemic risk levels. In most instances we find that the observed credit network significantly displays the highest systemic risk level. Lastly, we explore different policies to improve the robustness of the system.

Keywords: aggregation level, bipartite credit network, network reconstruction, stress testing, systemic risk

JEL Classification: G11, G20, G21, G28, G32

Suggested Citation

Ramadiah, Amanah and Caccioli, Fabio and Fricke, Daniel, Reconstructing and Stress Testing Credit Networks (September, 2018). ESRB: Working Paper Series No. 2018/84, Available at SSRN: https://ssrn.com/abstract=3723432 or http://dx.doi.org/10.2139/ssrn.3723432

Amanah Ramadiah (Contact Author)

University College London - Financial Computing and Analytics Group, Department of Computer Science ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Fabio Caccioli

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Daniel Fricke

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

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