Time series regression-based pairs trading in the Korean equities market
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Saejoon | - |
dc.contributor.author | Heo, Jun | - |
dc.date.accessioned | 2021-09-03T15:11:38Z | - |
dc.date.available | 2021-09-03T15:11:38Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 0952-813X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/86378 | - |
dc.description.abstract | Pairs trading is an instance of statistical arbitrage that relies on heavy quantitative data analysis to profit by capitalising low-risk trading opportunities provided by anomalies of related assets. A key element in pairs trading is the rule by which open and close trading triggers are defined. This paper investigates the use of time series regression to define the rule which has previously been identified with fixed threshold-based approaches. Empirical results indicate that our approach may yield significantly increased excess returns compared to ones obtained by previous approaches on large capitalisation stocks in the Korean equities market. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS LTD | - |
dc.subject | SUPPORT VECTOR MACHINES | - |
dc.subject | ARBITRAGE | - |
dc.title | Time series regression-based pairs trading in the Korean equities market | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Heo, Jun | - |
dc.identifier.doi | 10.1080/0952813X.2016.1259265 | - |
dc.identifier.scopusid | 2-s2.0-85006844208 | - |
dc.identifier.wosid | 000403013800006 | - |
dc.identifier.bibliographicCitation | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, v.29, no.4, pp.755 - 768 | - |
dc.relation.isPartOf | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE | - |
dc.citation.title | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE | - |
dc.citation.volume | 29 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 755 | - |
dc.citation.endPage | 768 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | SUPPORT VECTOR MACHINES | - |
dc.subject.keywordPlus | ARBITRAGE | - |
dc.subject.keywordAuthor | Pairs trading | - |
dc.subject.keywordAuthor | ARIMA | - |
dc.subject.keywordAuthor | SVR | - |
dc.subject.keywordAuthor | DTW | - |
dc.subject.keywordAuthor | cointegration | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
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.