Structural importance and evolution: an application to financial transaction networks

Isobel Seabrook, Paolo Barucca and Fabio Caccioli

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: A fundamental problem in the study of networks is the identification of important nodes. This is typically achieved using centrality metrics, which rank nodes in terms of their position in the network. This approach works well for static networks, that do not change over time, but does not consider the dynamics of the network. Here we propose instead to measure the importance of a node based on how much a change to its strength will impact the global structure of the network, which we measure in terms of the spectrum of its adjacency matrix. We apply our method to the identification of important nodes in equity transaction networks and show that, while it can still be computed from a static network, our measure is a good predictor of nodes subsequently transacting. This implies that static representations of temporal networks can contain information about their dynamics.

Keywords: node predictability; spectral perturbation; temporal network (search for similar items in EconPapers)
JEL-codes: C10 G00 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2022-12-01
New Economics Papers: this item is included in nep-ecm and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Physica A, 1, December, 2022, 607. ISSN: 0378-4371

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:117130

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