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dc.contributor.authorPhattanan Boonyanuphongen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-04T09:49:01Z-
dc.date.available2018-09-04T09:49:01Z-
dc.date.issued2014-01-01en_US
dc.identifier.issn21945357en_US
dc.identifier.other2-s2.0-84897874778en_US
dc.identifier.other10.1007/978-3-319-03395-2_26en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897874778&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/53427-
dc.description.abstractThis paper aims to study the structure of interdependencies between the energy, biofuel and agricultural commodity markets. The work concentrates on the dependence between ethanol and agricultural futures returns conditional to crude oil returns, and interdependence among agricultural commodities conditional to crude oil and ethanol futures returns. The C-vine copula based ARMA-GARCH model was used to explain the dependence structure of crude oil and the four related variables, and applied to investigate the risk of energy-agricultural commodity futures portfolio. We generally found symmetry in the tail dependence between the energy, biofuel, and agricultural commodities, and also found a greater significant variability in dependence, specifically, the dependence between the ethanol and agricultural commodity futures returns conditional to crude oil as well as interdependence between corn and soybean conditional to crude oil and ethanol return. This indicates that there is a rise in ethanol productions and that higher crude oil prices have caused a price increase in agricultural commodities such as corn and soybean. Moreover, the higher dynamic dependence and symmetric tail dependences indicate that opportunities for portfolio diversification are reduced, particularly during a downturn in the markets. Finally, our result suggests that the time-varying copula model captures the portfolio risk better than the static copula models. © Springer International Publishing Switzerland 2014.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleAn analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula modelen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume251en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsPrince of Songkla Universityen_US
Appears in Collections:CMUL: Journal Articles

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