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Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective
High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931700/ https://www.ncbi.nlm.nih.gov/pubmed/24586235 http://dx.doi.org/10.1371/journal.pone.0085018 |
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author | Fushing, Hsieh Chen, Shu-Chun Hwang, Chii-Ruey |
author_facet | Fushing, Hsieh Chen, Shu-Chun Hwang, Chii-Ruey |
author_sort | Fushing, Hsieh |
collection | PubMed |
description | High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing contrasting aggregation against sparsity of extreme events, is further compressed into a shortened sequence of state transitions. This compressed digital code sequence vividly demonstrates that the aggregation of large absolute returns is the primary driving force for stimulating both the aggregations of large trading volumes and transaction numbers. The state of system-wise synchrony is manifested with very frequent recurrence in the stock dynamics. And this data-driven dynamic mechanism is seen to correspondingly vary as the global market transiting in and out of contraction-expansion cycles. These results not only elaborate the stock dynamics of interest to a fuller extent, but also contradict some classical theories in finance. Overall this version of stock dynamics is potentially more coherent and realistic, especially when the current financial market is increasingly powered by high-frequency trading via computer algorithms, rather than by individual investors. |
format | Online Article Text |
id | pubmed-3931700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39317002014-02-25 Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective Fushing, Hsieh Chen, Shu-Chun Hwang, Chii-Ruey PLoS One Research Article High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS), and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing contrasting aggregation against sparsity of extreme events, is further compressed into a shortened sequence of state transitions. This compressed digital code sequence vividly demonstrates that the aggregation of large absolute returns is the primary driving force for stimulating both the aggregations of large trading volumes and transaction numbers. The state of system-wise synchrony is manifested with very frequent recurrence in the stock dynamics. And this data-driven dynamic mechanism is seen to correspondingly vary as the global market transiting in and out of contraction-expansion cycles. These results not only elaborate the stock dynamics of interest to a fuller extent, but also contradict some classical theories in finance. Overall this version of stock dynamics is potentially more coherent and realistic, especially when the current financial market is increasingly powered by high-frequency trading via computer algorithms, rather than by individual investors. Public Library of Science 2014-02-21 /pmc/articles/PMC3931700/ /pubmed/24586235 http://dx.doi.org/10.1371/journal.pone.0085018 Text en © 2014 Fushing 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Fushing, Hsieh Chen, Shu-Chun Hwang, Chii-Ruey Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title | Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title_full | Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title_fullStr | Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title_full_unstemmed | Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title_short | Single Stock Dynamics on High-Frequency Data: From a Compressed Coding Perspective |
title_sort | single stock dynamics on high-frequency data: from a compressed coding perspective |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931700/ https://www.ncbi.nlm.nih.gov/pubmed/24586235 http://dx.doi.org/10.1371/journal.pone.0085018 |
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