Multiplex Financial Networks


Multiplex Financial Networks


These are multilayer networks but not Hierarchical (multi-scale) networks.  This is one of latest research area in financial networks. Several research papers published in 2015 and current year are using multiplex networks to analyze multiple credit relationships in Interbank market.

  • Short term debt chains
  • Overnight debt chains
  • Long Term Debt chains
  • Collateral chains


From The multiplex structure of interbank networks


Network analysis has contributed to characterize, understand and model complex systems of interconnected financial institutions and markets (Gai and Kapadia, 2010; Battiston et al., 2012). These tools are gaining popu- larity also among policymakers. Most contributions focus on the interbank market1, the plumbing of modern financial systems, especially in the Euro area. In the network perspective, the interbank market is commonly rep- resented as a standard directed and weighted graph. Each link represents a credit relation between two counterparties. Directionality identifies the borrower and the lender; the weight of the link represents the loan amount. In general, the interbank market is much richer and complex than a simple weighted graph. In this paper we explore the differences in credit relations due to maturity of the contract or the presence of collateral. Due to lack of data availability, existing empirical literature either (i) disregards the hetero- geneity of credit relations or (ii) focuses only on one type, implicitly assuming that the network of the selected type of credit relations is a good proxy for the networks of other types. In the latter case, the vast majority of contributions focus on the overnight unsecured market. These two approaches are parsimo- nious but may provide biased results if the underlying “representativeness” assumptions fail.


From  Interbank markets and multiplex networks: centrality measures and statistical null models


Interlinkages between any two financial institutions is more complex than the information that can be summarized in a single number (the weight of the link) and a direction, such as in a directed and weighted network. This is due to the fact that between two institutions there exists a multiplicity of linkages, each of them related to one class of claims/obligations. The interplay between different types of relation could be relevant for systemic risk analysis. In the network jargon, such a situation is best modeled with a multiplex network or simply multiplex. A multiplex is made up with several ”layers”, each of them composed by all relations of the same type and modeled with a simple (possibly weighted and directed) network. Since the nodes in each layer are the same, the multiplex can be visualized as a stack of networks or equivalently by a network where several different types of links can coexist between two nodes, each type corresponding to a layer.


Key Sources of Research:


The multi-layer network nature of systemic risk and its implications for the costs of financial crises

Sebastian Poledna1, Jos ́e Luis Molina-Borboa4, Seraf ́ın Mart ́ınez-Jaramillo4, Marco van der Leij5,6,7, and Stefan Thurner


Using multiplex networks for banking systems dynamics modelling

Valentina Y. Guleva, Maria V. Skvorcova, and Alexander V. Boukhanovsky


Systemic risk in multiplex networks with asymmetric coupling and threshold feedback

Rebekka Burkholz, Matt V. Leduc, Antonios Garas & Frank Schweitzer


Networks of Networks: The Last Frontier of Complexity-A Book Review

Manuel Alberto M. Ferreira


Interconnected Networks

Editors: Garas, Antonios (Ed.)


Multilayer networks

Mikko Kivelä Alex Arenas Marc Barthelemy James P. Gleeson Yamir Moreno

and Mason A. Porter


Multi-layered Interbank Model for Assessing Systemic Risk

Mattia Montagna and Christoffer Kok


Nonlinear Dynamics on Interconnected Networks

Alex Arenas, Manlio De Domenico


The multiplex dependency structure of financial markets


Nicol ́o Musmeci,1 Vincenzo Nicosia,2 Tomaso Aste,3, 4 Tiziana Di Matteo,1, 3 and Vito Latora


Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks


Financial Contagion with Collateralized Transactions: A Multiplex Network Approach
Gustavo Peralta  Ricardo Crisóstomo

July 2016


The multiplex structure of interbank networks

L. Bargigli,a G. di Iasio,b L. Infante,c F. Lillo,d F. Pierobone

November 20, 2013


Interbank markets and multiplex networks: centrality measures and statistical null models

Leonardo Bargigli, Giovanni di Iasio, Luigi Infante, Fabrizio Lillo and Federico Pierobon


Strength of weak layers in cascading failures on multiplex networks: case of the international trade network

Kyu-Min Lee & K.-I. Goh



 Cascades in multiplex financial networks with debts of different seniority

Charles D. Brummitt

Teruyoshi Kobayashi


Multiplex interbank networks and systemic importance An application to European data

In ̃aki Aldasoro† Iva ́n Alves‡

May 2015


Control of Multilayer Networks

Giulia Menichetti1, Luca Dall’Asta2,3 & Ginestra Bianconi


Centrality Measurement of the Mexican Large Value Payments System from the Perspective of Multiplex Networks

Bernardo Bravo-Benitez, Biliana Alexandrova-Kabadjova, Serafin Martinez-Jaramillo



Recent advances on failure and recovery in networks of networks

Louis M. Shekhtman∗, Michael M. Danziger, Shlomo Havlin


Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures

Carlos León  Ron J. Berndsen   Luc Renneboog


The structure and dynamics of multilayer networks

S. Boccaletti,∗, G. Bianconic, R. Criadod,, C.I. del Geniof,, J. Gómez-Gardeñes, M. Romanced, Sendiña-Nadal, Z. Wang. Zaninm,


A multi-layer network of the sovereign securities market

Carlos León  Jhonatan Pérez  Luc Renneboog


Growing Multiplex Networks with Arbitrary Number of Layers

Babak Fotouhi1 and Naghmeh Momeni



Quantitative Finance

Special Issue on Interlinkages & Systemic Risk







Author: Mayank Chaturvedi

You can contact me using this email mchatur at the rate of AOL.COM. My professional profile is on

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