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dc.contributor.authorMichael McAleeren_US
dc.contributor.authorChatayan Wiphatthanananthakulen_US
dc.date.accessioned2018-09-04T04:44:47Z-
dc.date.available2018-09-04T04:44:47Z-
dc.date.issued2010-06-01en_US
dc.identifier.issn03784754en_US
dc.identifier.other2-s2.0-77953324993en_US
dc.identifier.other10.1016/j.matcom.2010.04.001en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77953324993&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/50727-
dc.description.abstractIn 2003, the Chicago Board Options Exchange (CBOE) made two key enhancements to the volatility index (VIX) methodology based on S&P options. The new VIX methodology seems to be based on a complicated formula to calculate expected volatility. In this paper, with the use of Thailand's SET50 Index Options data, we modify the VIX formula to a very simple relationship, which has a higher negative correlation between the VIX for Thailand (TVIX) and SET50 index options. We show that TVIX provides more accurate forecasts of option prices than the simple expected volatility (SEV) index, but the SEV index outperforms TVIX in forecasting expected volatility. Therefore, the SEV index would seem to be a superior tool as a hedging diversification tool because of the high negative correlation with the volatility index. Crown Copyright © 2010.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleA simple expected volatility (SEV) index: Application to SET50 index optionsen_US
dc.typeJournalen_US
article.title.sourcetitleMathematics and Computers in Simulationen_US
article.volume80en_US
article.stream.affiliationsErasmus School of Economicsen_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsChulachomklao Royal Military Academyen_US
Appears in Collections:CMUL: Journal Articles

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