Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/452725
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dc.coverage.spatialDecision Sciences
dc.date.accessioned2023-01-24T11:56:17Z-
dc.date.available2023-01-24T11:56:17Z-
dc.identifier.urihttp://hdl.handle.net/10603/452725-
dc.description.abstractThe four essays in this dissertation are grounded in the central and interconnected concepts of multifractality and long-range dependence observed in financial time series. We focus our attention particularly to the dependence behavior of a suitable measure of volatility in financial asset returns. Therefore, the implications of our work are mostly in the area of financial risk management. newline
dc.format.extent107p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleTime series clustering testing of memory in time series and quantifying dependence in volatility of financial time series using complex network theory
dc.title.alternative
dc.creator.researcherAchari, Giriraj
dc.subject.keywordBusiness Finance
dc.subject.keywordEconomics and Business
dc.subject.keywordSocial Sciences
dc.description.noteAbstract page no.6
dc.contributor.guideBhattacharyya, Malay and Murthy, Rajluxmi V
dc.publisher.placeBangalore
dc.publisher.universityIndian Institute of Management Bangalore
dc.publisher.institutionDecision Sciences
dc.date.registered2017
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Decision Sciences



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