Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58537
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dc.contributor.authorPichayakone Rakphoen_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorRoengchai Tansuchaten_US
dc.date.accessioned2018-09-05T04:26:02Z-
dc.date.available2018-09-05T04:26:02Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85037837990en_US
dc.identifier.other10.1007/978-3-319-70942-0_39en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037837990&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58537-
dc.description.abstract© Springer International Publishing AG 2018. The price of precious metals is highly volatile and it can bring both risk and fortune to traders and investors, and therefore should be examined. In this paper, we introduce an approach to fitting a Copula-GARCH to valued time series and apply this methodology to the daily histogram returns of precious metals consisting of gold, silver, and platinum. The study also conducts a simulation study to confirm the accuracy of the model and the result shows that our model performs well. In the empirical study, our results suggest investing on gold and platinum in high proportion while silver is not recommended for inclusion in the precious metal portfolio. Moreover, precious metal portfolio of the intraday 30-min returns gives lower risk when compared with portfolio of the intraday 60-min returns. Therefore, investors should not hold assets for long period of time because the long-term holding is likely to face a higher risk.en_US
dc.subjectComputer Scienceen_US
dc.titleRisk valuation of precious metal returns by histogram valued time seriesen_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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