research-article

The Multiplex Dependency Structure of Financial Markets

Authors:

Nicolò Musmeci,

Vincenzo Nicosia,

Tiziana Di Matteo,

Vito Latora Academic Editor:

Tommaso GiliAuthors Info & Claims

Complexity, Volume 2017

https://doi.org/10.1155/2017/9586064

Published: 01 January 2017 Publication History

Abstract

We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex datasets. In particular, we consider multiplex networks made of four layers corresponding, respectively, to linear, nonlinear, tail, and partial correlations among a set of financial time series. We construct the sparse graph on each layer using a standard network filtering procedure, and we then analyse the structural properties of the obtained multiplex networks. The study of the time evolution of the multiplex constructed from financial data uncovers important changes in intrinsically multiplex properties of the network, and such changes are associated with periods of financial stress. We observe that some features are unique to the multiplex structure and would not be visible otherwise by the separate analysis of the single-layer networks corresponding to each dependency measure.

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Cited By

Castilho DSouza TKang SGama Jde Carvalho A(2024)Forecasting financial market structure from network features using machine learningKnowledge and Information Systems10.1007/s10115-024-02095-666:8(4497-4525)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10115-024-02095-6
Liu YHu CWang LYang K(2020)Multilayer Network Risk Factor Pricing ModelComplexity10.1155/2020/66188532020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/6618853

Index Terms

The Multiplex Dependency Structure of Financial Markets

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

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Published In

cover image Complexity

Complexity Volume 2017, Issue

2017

3175 pages

ISSN:1076-2787

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Copyright © 2017 Nicolò Musmeci et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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John Wiley & Sons, Inc.

United States

Publication History

Published: 01 January 2017

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Cited By

Castilho DSouza TKang SGama Jde Carvalho A(2024)Forecasting financial market structure from network features using machine learningKnowledge and Information Systems10.1007/s10115-024-02095-666:8(4497-4525)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10115-024-02095-6
Liu YHu CWang LYang K(2020)Multilayer Network Risk Factor Pricing ModelComplexity10.1155/2020/66188532020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/6618853

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