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A robust filter in stock networks analysis

We show that the use of a minimal spanning tree (MST) to filter important information in a complex system is not robust except when the system contains a unique MST. In this paper we propose to use the forest of all MSTs as a robust filter. According to this filter, centrality measures are also robu...

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Main Author: Djauhari, Maman Abdurachman
Format: Article
Published: 2012
Subjects:
QC Physics
Online Access:http://eprints.utm.my/id/eprint/46529/
https://dx.doi.org/10.1016/j.physa.2012.05.060
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spelling my.utm.465292017-09-12T07:41:13Z http://eprints.utm.my/id/eprint/46529/ A robust filter in stock networks analysis Djauhari, Maman Abdurachman QC Physics We show that the use of a minimal spanning tree (MST) to filter important information in a complex system is not robust except when the system contains a unique MST. In this paper we propose to use the forest of all MSTs as a robust filter. According to this filter, centrality measures are also robust. For that purpose an algorithm, which can also be used to detect the uniqueness of an MST, will be provided. A simple hypothetical example will clarify the construction of the proposed filter and a real problem in filtering the information contained in NYSE 100 stocks will illustrate its advantages compared to the MST-based filter 2012 Article PeerReviewed Djauhari, Maman Abdurachman (2012) A robust filter in stock networks analysis. Physica A: Statistical Mechanics and its Applications, 391 . pp. 5049-5057. ISSN 0378-4271 https://dx.doi.org/10.1016/j.physa.2012.05.060
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QC Physics
spellingShingle QC Physics
Djauhari, Maman Abdurachman
A robust filter in stock networks analysis
description We show that the use of a minimal spanning tree (MST) to filter important information in a complex system is not robust except when the system contains a unique MST. In this paper we propose to use the forest of all MSTs as a robust filter. According to this filter, centrality measures are also robust. For that purpose an algorithm, which can also be used to detect the uniqueness of an MST, will be provided. A simple hypothetical example will clarify the construction of the proposed filter and a real problem in filtering the information contained in NYSE 100 stocks will illustrate its advantages compared to the MST-based filter
format Article
author Djauhari, Maman Abdurachman
author_facet Djauhari, Maman Abdurachman
author_sort Djauhari, Maman Abdurachman
title A robust filter in stock networks analysis
title_short A robust filter in stock networks analysis
title_full A robust filter in stock networks analysis
title_fullStr A robust filter in stock networks analysis
title_full_unstemmed A robust filter in stock networks analysis
title_sort robust filter in stock networks analysis
publishDate 2012
url http://eprints.utm.my/id/eprint/46529/
https://dx.doi.org/10.1016/j.physa.2012.05.060
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score 13.211869

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