Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58527
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dc.contributor.authorRungrapee Phadkanthaen_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorRoengchai Tansuchaten_US
dc.date.accessioned2018-09-05T04:25:57Z-
dc.date.available2018-09-05T04:25:57Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85037867938en_US
dc.identifier.other10.1007/978-3-319-70942-0_38en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037867938&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58527-
dc.description.abstract© Springer International Publishing AG 2018. This study introduces an approach to fitting a copula based seemingly unrelated regression to an interval-valued data set. This approach consists of fitting a model on the appropriate point of the interval values assumed by the variables in the learning set. To find the appropriate point of the interval values, we assign weights in calculating the appropriate value between intervals by using convex combination method. We apply this methodology to quantify the risk and dependence of Real Estate Investment Trust (REITs) in Asia. Our results suggest that Hong Kong and Japan markets have a positive sign of the beta and both markets have less volatility than the global REITs market. On the other hand, we find that the estimated beta for Singapore market shows a negative relationship with global REITs market. We conclude that Singapore market can be viewed as a hedge against higher risk in Asian REITs.en_US
dc.subjectComputer Scienceen_US
dc.titleAnalysis of risk, rate of return and dependency of REITs in ASIA with capital asset pricing modelen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume753en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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