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dc.contributor.supervisorThavaneswaran, Aerambamoorthy (Statistics) Ghahramani, Melody (Statistics)en_US
dc.contributor.authorDoshi, Ankit
dc.date.accessioned2012-09-20T13:55:35Z
dc.date.available2012-09-20T13:55:35Z
dc.date.issued2011-03en_US
dc.identifier.citationDoshi, A., Frank, J. and Thavaneswaran, A. (2011). Seasonal volatility models. Journal of Statistical Theory and Applications, 10, 1-10.en_US
dc.identifier.urihttp://hdl.handle.net/1993/8889
dc.description.abstractGARCH models have been widely used in finance to model volatility ever since the introduction of the ARCH model and its extension to the generalized ARCH (GARCH) model. Lately, there has been growing interest in modelling seasonal volatility, most recently with the introduction of the multiplicative seasonal GARCH models. As an application of the multiplicative seasonal GARCH model with real data, call prices from the major stock market index of India are calculated using estimated parameter values. It is shown that a multiplicative seasonal GARCH option pricing model outperforms the Black-Scholes formula and a GARCH(1,1) option pricing formula. A parametric bootstrap procedure is also employed to obtain an interval approximation of the call price. Narrower confidence intervals are obtained using the multiplicative seasonal GARCH model than the intervals provided by the GARCH(1,1) model for data that exhibits multiplicative seasonal GARCH volatility.en_US
dc.language.isoengen_US
dc.publisherGowas Publishing Houseen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectOption pricingen_US
dc.subjectSeasonalityen_US
dc.subjectVolatilityen_US
dc.subjectGARCHen_US
dc.subjectKurtosisen_US
dc.subjectBootstrapen_US
dc.subjectBrownian motionen_US
dc.subjectBlack-Scholesen_US
dc.titleSeasonal volatility models with applications in option pricingen_US
dc.typeinfo:eu-repo/semantics/masterThesis
dc.typemaster thesisen_US
dc.degree.disciplineStatisticsen_US
dc.contributor.examiningcommitteeMuthukumarana, Saman (Statistics) Rajapakse, Athula (Electrical & Computer Engineering)en_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.noteOctober 2012en_US


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