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dc.contributor.authorRoengchai Tansuchaten_US
dc.contributor.authorParavee Maneejuken_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstract© Published under licence by IOP Publishing Ltd. We propose a multivariate copulas based seemingly unrelated quantile regression. We add the multivariate copula density function into the likelihood to relax the strong assumption of multivariate normal distribution of the conventional model. The simulation study is conducted to evaluate the performance of our proposed model. Moreover, we apply our proposed model to the Fama-French equation in order to investigate the systematic risk in the three major stocks in NASDAQ market. The results of this study suggest that our proposed model provides a particularly good description of these stock prices at every quantile level.en_US
dc.subjectPhysics and Astronomyen_US
dc.titleCopulas based seemingly unrelated quantile regressionen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleJournal of Physics: Conference Seriesen_US
article.volume1053en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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