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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Main Authors: Sindhuja Ranganathan, Mikko Kivelä, Juho Kanniainen
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0198807
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author Sindhuja Ranganathan
Mikko Kivelä
Juho Kanniainen
author_facet Sindhuja Ranganathan
Mikko Kivelä
Juho Kanniainen
author_sort Sindhuja Ranganathan
collection DOAJ
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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publishDate 2018-01-01
publisher Public Library of Science (PLoS)
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spelling doaj-art-0c4cd1aedd3a42928c70033f16f608ed2025-08-20T02:03:47ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019880710.1371/journal.pone.0198807Dynamics of investor spanning trees around dot-com bubble.Sindhuja RanganathanMikko KiveläJuho KanniainenWe 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.https://doi.org/10.1371/journal.pone.0198807
spellingShingle Sindhuja Ranganathan
Mikko Kivelä
Juho Kanniainen
Dynamics of investor spanning trees around dot-com bubble.
PLoS ONE
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
url https://doi.org/10.1371/journal.pone.0198807
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AT mikkokivela dynamicsofinvestorspanningtreesarounddotcombubble
AT juhokanniainen dynamicsofinvestorspanningtreesarounddotcombubble