Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58530
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dc.contributor.authorPathairat Pastpipatkulen_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:25:58Z-
dc.date.available2018-09-05T04:25:58Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85038845507en_US
dc.identifier.other10.1007/978-3-319-73150-6_55en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85038845507&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58530-
dc.description.abstract© 2018, Springer International Publishing AG. The paper aims to measure the risk and find the optimal weights of portfolio containing three instruments: Stock Exchange of Thailand, Thai Baht gold, and Treasury 10-year bond yield. The study employs the C-D vine copulas approach to construct the dependency of each pair instruments and uses the Monte Carlo simulation technique to generate the simulated data to compute Value at Risk (VaR) and Expected Shortfall (ES). Our results show that there exists a weak significant dependency between Stock Exchange of Thailand index and Thai Baht gold and dependency between Treasury 10-year bond yield and Thai Baht gold. Moreover, we find that the desired portfolio allocation is 49.8% of SET, 18.8% of Bond, and 31.4% of Gold where risk and return of the portfolio are 2.7% and 0.05%, respectively.en_US
dc.subjectComputer Scienceen_US
dc.titlePortfolio selection with stock, gold and bond in Thailand under vine copulas functionsen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume760en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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