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dc.contributor.authorTanaporn Tungtrakulen_US
dc.contributor.authorNatthaphat Kingnetren_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstract© Springer International Publishing AG 2017. This study investigates the exchange rate volatility of Thai baht using GARCH, TGARCH, EGARCH and PGARCH models and examines the robustness of these models under different mean equation specifications. The data consisted of monthly exchange rate of Thai baht with five currencies of leading trade partners during January 2002-March 2016. The results show that the GARCH model is well-fitted for Chinese yuan and US dollar exchange rate, while TGARCH model is suitable to be selected for Japanese yen, Malaysian ringgit and Singapore dollar. For the model sensitivity, the findings indicate that the GARCH model is robust for the cases of Chinese yuan and US dollar, while TGARCH model is robust only for Malaysian ringgit. Therefore, We conclude that the selection of GARCH models is sensitive to mean equation specification. This confirms that researchers should pay attention to mean equation specifications when it comes to volatility modelling.en_US
dc.subjectComputer Scienceen_US
dc.titleDo we have robust GARCH models under different mean equations: Evidence from exchange rates of thailand?en_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume692en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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