Journal of Network Theory in Finance

Risk.net

In search of lost edges: a case study on reconstructing financial networks

Michael Lebacher, Samantha Cook, Nadja Klein and Göran Kauermann

• In this paper, different network reconstruction methods are compared using a payment network.

• The performance of different methods varies strongly, depending on their usage for the reconstruction of binary or valued networks.

• There exists no standard solution that is able to reconstruct all properties of a network equally well.

• If exogenous information is available it should be used to increase the predictive quality.

In this paper, we review the different methods designed to estimate matrixes from their marginals and potentially exogenous information. This includes a general discussion of the available methodology, which provides edge probabilities and models that are focused on the reconstruction of edge values. Besides summarizing their advantages and shortfalls, we conduct a competitive comparison of the approaches using Society for Worldwide Interbank Financial Telecommunication (SWIFT) MT 103 single customer credit transfers. The comparison concerning the binary reconstruction is divided into an evaluation of the edge probabilities and of the accuracy of the predicted edge values. To test the methods on different topologies, the application is split into two parts. The first part considers the full MT 103 network, providing an illustration of the reconstruction of large, sparse financial networks. The second part is concerned with reconstructing a subset of the full network, representing a dense medium-sized network. Regarding substantial outcomes, it is found that there are some methods that do work well in many respects. However, that does not imply that a certain method is generally superior. In general, the preferred model choice highly depends on the goal of the analysis, the presumed network structure and the availability of exogenous information.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Risk.net? View our subscription options

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here