Fractal structure in the S&P500: A correlation -based threshold network approach
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ku, Seungmo | - |
dc.contributor.author | Lee, Changju | - |
dc.contributor.author | Chang, Woojin | - |
dc.contributor.author | Song, Jae Wook | - |
dc.date.accessioned | 2022-07-07T17:27:14Z | - |
dc.date.available | 2022-07-07T17:27:14Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2020-08 | - |
dc.identifier.issn | 0960-0779 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/145289 | - |
dc.description.abstract | This research aims to analyze the S&P500 network, one of the representatives of the global financial market, based on its network fractality. The research is conducted in the following steps. At first, we propose the concept of a correlation-based threshold network based on minimum spanning tree. Secondly, we investigate the fractal dimension of threshold networks and propose suitable fractal dimension measures. Lastly, we analyze the S&P500 network based on the proposed measures and utilize them in the market prediction. Based on the results, we discover the self-similarity characteristic of the S&P500 network, where a strong effective repulsion phenomenon is detected. Furthermore, we observe the different growth patterns of S&P500 network for different combinations of fractal conditions defined by the proposed measures. Then, we utilize the measures in the prediction of the cumulative log-return of S&P500 index via a simple artificial neural network and detect the improvement of prediction performance in the long-term development of the market. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.title | Fractal structure in the S&P500: A correlation -based threshold network approach | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Song, Jae Wook | - |
dc.identifier.doi | 10.1016/j.chaos.2020.109848 | - |
dc.identifier.scopusid | 2-s2.0-85084702174 | - |
dc.identifier.wosid | 000541452300011 | - |
dc.identifier.bibliographicCitation | CHAOS SOLITONS & FRACTALS, v.137, pp.1 - 15 | - |
dc.relation.isPartOf | CHAOS SOLITONS & FRACTALS | - |
dc.citation.title | CHAOS SOLITONS & FRACTALS | - |
dc.citation.volume | 137 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 15 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Physics, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Physics, Mathematical | - |
dc.subject.keywordPlus | DIMENSION | - |
dc.subject.keywordPlus | RETURNS | - |
dc.subject.keywordPlus | MINIMUM | - |
dc.subject.keywordPlus | ENTROPY | - |
dc.subject.keywordPlus | GROWTH | - |
dc.subject.keywordPlus | TOOL | - |
dc.subject.keywordAuthor | Fractal dimension | - |
dc.subject.keywordAuthor | Market prediction | - |
dc.subject.keywordAuthor | Strong effective repulsion | - |
dc.subject.keywordAuthor | Threshold network | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0960077920302484?via%3Dihub | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.