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Systemic risk from investment similarities
Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bip...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533041/ https://www.ncbi.nlm.nih.gov/pubmed/31120950 http://dx.doi.org/10.1371/journal.pone.0217141 |
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author | Delpini, Danilo Battiston, Stefano Caldarelli, Guido Riccaboni, Massimo |
author_facet | Delpini, Danilo Battiston, Stefano Caldarelli, Guido Riccaboni, Massimo |
author_sort | Delpini, Danilo |
collection | PubMed |
description | Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and study the diversification, as understood in modern portfolio theory, and the similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from benchmark models of random allocation of investments. This indicates the existence of strong correlations between fund investment strategies. We exploit a deliberately simplified model of shock propagation to identify a systemic risk component stemming from the similarity of portfolios. The network is still partially vulnerable after the crisis because of this effect, despite the increase in the diversification of multi asset portfolios. Diversification and similarity should be taken into account jointly to properly assess systemic risk. |
format | Online Article Text |
id | pubmed-6533041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65330412019-06-05 Systemic risk from investment similarities Delpini, Danilo Battiston, Stefano Caldarelli, Guido Riccaboni, Massimo PLoS One Research Article Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and study the diversification, as understood in modern portfolio theory, and the similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from benchmark models of random allocation of investments. This indicates the existence of strong correlations between fund investment strategies. We exploit a deliberately simplified model of shock propagation to identify a systemic risk component stemming from the similarity of portfolios. The network is still partially vulnerable after the crisis because of this effect, despite the increase in the diversification of multi asset portfolios. Diversification and similarity should be taken into account jointly to properly assess systemic risk. Public Library of Science 2019-05-23 /pmc/articles/PMC6533041/ /pubmed/31120950 http://dx.doi.org/10.1371/journal.pone.0217141 Text en © 2019 Delpini et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Delpini, Danilo Battiston, Stefano Caldarelli, Guido Riccaboni, Massimo Systemic risk from investment similarities |
title | Systemic risk from investment similarities |
title_full | Systemic risk from investment similarities |
title_fullStr | Systemic risk from investment similarities |
title_full_unstemmed | Systemic risk from investment similarities |
title_short | Systemic risk from investment similarities |
title_sort | systemic risk from investment similarities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533041/ https://www.ncbi.nlm.nih.gov/pubmed/31120950 http://dx.doi.org/10.1371/journal.pone.0217141 |
work_keys_str_mv | AT delpinidanilo systemicriskfrominvestmentsimilarities AT battistonstefano systemicriskfrominvestmentsimilarities AT caldarelliguido systemicriskfrominvestmentsimilarities AT riccabonimassimo systemicriskfrominvestmentsimilarities |