EURO 2025 Leeds
Abstract Submission

1529. Resilience of multilayer networks through community detection with a portfolio stability application

Invited abstract in session TB-9: Complexity in finance, stream OR in Finance and Insurance .

Tuesday, 10:30-12:00
Room: Clarendon SR 2.01

Authors (first author is the speaker)

1. saverio storani
Sapienza
2. Roy Cerqueti
Department of Social and Economic Sciences, Sapienza University of Rome
3. Raffaele Mattera
University of Campania Luigi Vanvitelli

Abstract

Network resilience is a key concept in complex network theory, extensively studied from both theoretical and applied perspectives. While resilience has been widely explored in monolayer networks, its implications in multilayer structures remain underdeveloped. In this paper, we contribute to this debate by introducing a novel resilience measure for multilayer networks, based on community detection applied within individual layers. Specifically, we model a multilayer network where nodes are connected through multidimensional attributes, with intralayer links determined by attribute similarity and interlayer links established via hierarchical clustering.

To assess resilience, we define external shocks that alter the network’s structure. Shock type 1 isolates a node by modifying its community assignment, while shock type 2 removes interlayer connections, inducing structural changes. We measure resilience by quantifying variations in the community configuration following these perturbations.

As an application, we examine the resilience of financial multilayer networks, where layers represent key asset characteristics: expected returns, conditional variances, and unconditional correlations. Using distance measures tailored to each financial attribute, we construct a multilayer structure and analyze its stability under shocks. Our findings provide insights into the robustness of financial systems and the role of individual assets in network destabilization.

Keywords

Status: accepted

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