Adjustable Network Reconstruction with Applications to CDS Exposures

21 Pages Posted: 10 Jan 2017 Last revised: 27 Apr 2018

See all articles by Axel Gandy

Axel Gandy

Imperial College London - Department of Mathematics

Luitgard Anna Maria Veraart

London School of Economics & Political Science (LSE) - Department of Mathematics

Date Written: April 25, 2017

Abstract

This paper is concerned with reconstructing weighted directed networks from the total in- and out-weight of each node. This problem arises for example in the analysis of systemic risk of partially observed financial networks. Typically a wide range of networks is consistent with this partial information. We develop an empirical Bayesian methodology that can be adjusted such that the resulting networks are consistent with the observations and satisfy certain desired global topological properties such as a given mean density, extending the approach by Gandy and Veraart (2017). Furthermore we propose a new fitness based model within this framework. We provide a case study based on a data set consisting of 89 fully observed financial networks of credit default swap exposures. We reconstruct those networks based on only partial information using the newly proposed as well as existing methods. To assess the quality of the reconstruction, we use a wide range of criteria, including measures on how well the degree distribution can be captured and higher order measures on systemic risk. We find that the empirical Bayesian approach performs best.

Keywords: Bayesian methods, random graphs, matrix balancing, systemic risk

JEL Classification: C11, C15, C63, C88, G01

Suggested Citation

Gandy, Axel and Veraart, Luitgard Anna Maria, Adjustable Network Reconstruction with Applications to CDS Exposures (April 25, 2017). Available at SSRN: https://ssrn.com/abstract=2895754 or http://dx.doi.org/10.2139/ssrn.2895754

Axel Gandy

Imperial College London - Department of Mathematics ( email )

South Kensington Campus
Imperial College
LONDON, SW7 2AZ
United Kingdom

Luitgard Anna Maria Veraart (Contact Author)

London School of Economics & Political Science (LSE) - Department of Mathematics ( email )

Houghton Street
GB-London WC2A 2AE
United Kingdom

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