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Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets
The concept of “Structural Diversity” of a network refers to the level of dissimilarity between the various agents acting in the system, and it is typically interpreted as the number of connected components in the network. This key property of networks has been studied in multiple settings, includin...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658667/ https://www.ncbi.nlm.nih.gov/pubmed/31346204 http://dx.doi.org/10.1038/s41598-019-47210-8 |
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author | Almog, Assaf Shmueli, Erez |
author_facet | Almog, Assaf Shmueli, Erez |
author_sort | Almog, Assaf |
collection | PubMed |
description | The concept of “Structural Diversity” of a network refers to the level of dissimilarity between the various agents acting in the system, and it is typically interpreted as the number of connected components in the network. This key property of networks has been studied in multiple settings, including diffusion of ideas in social networks and functional diversity of regions in brain networks. Here, we propose a new measure, “Structural Entropy”, as a revised interpretation to “Structural Diversity”. The proposed measure relies on the finer-grained network communities (in contrast to the network’s connected components), and takes into consideration both the number of communities and their sizes, generating a single representative value. We then propose an approach for monitoring the structure of correlation-based networks over time, which relies on the newly suggested measure. Finally, we illustrate the usefulness of the new approach, by applying it to the particular case of emergent organization of financial markets. This provides us a way to explore their underlying structural changes, revealing a remarkably high linear correlation between the new measure and the volatility of the assets’ prices over time. |
format | Online Article Text |
id | pubmed-6658667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66586672019-07-31 Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets Almog, Assaf Shmueli, Erez Sci Rep Article The concept of “Structural Diversity” of a network refers to the level of dissimilarity between the various agents acting in the system, and it is typically interpreted as the number of connected components in the network. This key property of networks has been studied in multiple settings, including diffusion of ideas in social networks and functional diversity of regions in brain networks. Here, we propose a new measure, “Structural Entropy”, as a revised interpretation to “Structural Diversity”. The proposed measure relies on the finer-grained network communities (in contrast to the network’s connected components), and takes into consideration both the number of communities and their sizes, generating a single representative value. We then propose an approach for monitoring the structure of correlation-based networks over time, which relies on the newly suggested measure. Finally, we illustrate the usefulness of the new approach, by applying it to the particular case of emergent organization of financial markets. This provides us a way to explore their underlying structural changes, revealing a remarkably high linear correlation between the new measure and the volatility of the assets’ prices over time. Nature Publishing Group UK 2019-07-25 /pmc/articles/PMC6658667/ /pubmed/31346204 http://dx.doi.org/10.1038/s41598-019-47210-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Almog, Assaf Shmueli, Erez Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title | Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title_full | Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title_fullStr | Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title_full_unstemmed | Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title_short | Structural Entropy: Monitoring Correlation-Based Networks Over Time With Application To Financial Markets |
title_sort | structural entropy: monitoring correlation-based networks over time with application to financial markets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658667/ https://www.ncbi.nlm.nih.gov/pubmed/31346204 http://dx.doi.org/10.1038/s41598-019-47210-8 |
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