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DC Field | Value | Language |
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dc.contributor.author | Kongliang Zhu | en_US |
dc.contributor.author | Woraphon Yamaka | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2018-09-05T02:57:55Z | - |
dc.date.available | 2018-09-05T02:57:55Z | - |
dc.date.issued | 2016-01-01 | en_US |
dc.identifier.issn | 16113349 | en_US |
dc.identifier.issn | 03029743 | en_US |
dc.identifier.other | 2-s2.0-85006070940 | en_US |
dc.identifier.other | 10.1007/978-3-319-49046-5_50 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006070940&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/55563 | - |
dc.description.abstract | © Springer International Publishing AG 2016. Pairs trading strategy is a famous strategy and commonly taken by many investors. There are various approaches to define the pairs trading signal which is the important part of the strategy. This study aims to propose an alternative approach, Markov Switching Regression GARCH model, to specify the trading signal for stock pair taking into account the structural change in the pair return. We applied our proposed model to the Stock Exchange of Thailand and the result shows our pairs trading strategy is relatively more effective for financial investment management compared with the single mean return from individual stock method. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Mathematics | en_US |
dc.title | Pair trading rule with switching regression GARCH model | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
article.volume | 9978 LNAI | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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