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Dynamics of investor spanning trees around dot-com bubble

We identify temporal investor networks for Nokia stock by constructing networks from correlations between investor-specific net-volumes and analyze changes in the networks around dot-com bubble. The analysis is conducted separately for households, financial, and non-financial institutions. Our resul...

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Detalles Bibliográficos
Autores principales: Ranganathan, Sindhuja, Kivelä, Mikko, Kanniainen, Juho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5999117/
https://www.ncbi.nlm.nih.gov/pubmed/29897973
http://dx.doi.org/10.1371/journal.pone.0198807
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author Ranganathan, Sindhuja
Kivelä, Mikko
Kanniainen, Juho
author_facet Ranganathan, Sindhuja
Kivelä, Mikko
Kanniainen, Juho
author_sort Ranganathan, Sindhuja
collection PubMed
description We identify temporal investor networks for Nokia stock by constructing networks from correlations between investor-specific net-volumes and analyze changes in the networks around dot-com bubble. The analysis is conducted separately for households, financial, and non-financial institutions. Our results indicate that spanning tree measures for households reflected the boom and crisis: the maximum spanning tree measures had a clear upward tendency in the bull markets when the bubble was building up, and, even more importantly, the minimum spanning tree measures pre-reacted the burst of the bubble. At the same time, we find less clear reactions in the minimal and maximal spanning trees of non-financial and financial institutions around the bubble, which suggests that household investors can have a greater herding tendency around bubbles.
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spelling pubmed-59991172018-06-21 Dynamics of investor spanning trees around dot-com bubble Ranganathan, Sindhuja Kivelä, Mikko Kanniainen, Juho PLoS One Research Article We identify temporal investor networks for Nokia stock by constructing networks from correlations between investor-specific net-volumes and analyze changes in the networks around dot-com bubble. The analysis is conducted separately for households, financial, and non-financial institutions. Our results indicate that spanning tree measures for households reflected the boom and crisis: the maximum spanning tree measures had a clear upward tendency in the bull markets when the bubble was building up, and, even more importantly, the minimum spanning tree measures pre-reacted the burst of the bubble. At the same time, we find less clear reactions in the minimal and maximal spanning trees of non-financial and financial institutions around the bubble, which suggests that household investors can have a greater herding tendency around bubbles. Public Library of Science 2018-06-13 /pmc/articles/PMC5999117/ /pubmed/29897973 http://dx.doi.org/10.1371/journal.pone.0198807 Text en © 2018 Ranganathan 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
Ranganathan, Sindhuja
Kivelä, Mikko
Kanniainen, Juho
Dynamics of investor spanning trees around dot-com bubble
title Dynamics of investor spanning trees around dot-com bubble
title_full Dynamics of investor spanning trees around dot-com bubble
title_fullStr Dynamics of investor spanning trees around dot-com bubble
title_full_unstemmed Dynamics of investor spanning trees around dot-com bubble
title_short Dynamics of investor spanning trees around dot-com bubble
title_sort dynamics of investor spanning trees around dot-com bubble
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5999117/
https://www.ncbi.nlm.nih.gov/pubmed/29897973
http://dx.doi.org/10.1371/journal.pone.0198807
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