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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/36183
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dc.contributor.authorElliott, R.-
dc.contributor.authorMiao, H.-
dc.date.issued2006-
dc.identifier.citationStochastic Analysis and Applications, 2006; 24(3):661-683-
dc.identifier.issn0736-2994-
dc.identifier.issn1532-9356-
dc.identifier.urihttp://hdl.handle.net/2440/36183-
dc.descriptionCopyright © Taylor & Francis Group, LLC-
dc.description.abstractWe generalize the stochastic volatility model by allowing the volatility to follow different dynamics in different states of the world. The dynamics of the "states of the world" are represented by a Markov chain. We estimate all the parameters by using the filtering and the EM algorithms. Closed form estimates for all parameters are derived in this paper. These estimates can be updated using new information as it arrives.-
dc.description.statementofresponsibilityRobert J. Elliott; Hong Miao-
dc.language.isoen-
dc.publisherMarcel Dekker Inc-
dc.source.urihttp://www.informaworld.com/smpp/content?content=10.1080/07362990600629389-
dc.subjectEM algorithm-
dc.subjectFiltering-
dc.subjectMarkov switching-
dc.subjectStochastic volatility.-
dc.titleStochastic volatility model with filtering-
dc.typeJournal article-
dc.identifier.doi10.1080/07362990600629389-
pubs.publication-statusPublished-
Appears in Collections:Applied Mathematics publications
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