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dc.contributor.advisorYiğit, Taner
dc.contributor.authorAksu, Gülşah
dc.date.accessioned2016-01-08T18:12:30Z
dc.date.available2016-01-08T18:12:30Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/11693/15043
dc.descriptionAnkara : The Department of Economics, Bilkent University, 2010.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2010.en_US
dc.descriptionIncludes bibliographical references leaves 35-36.en_US
dc.description.abstractThe understanding of bond yields is important for several reasons such as forecasting, monetary and debt policies, derivative pricing and investment decisions. The existence of a huge literature on this subject is a clue on how lots of researchers are trying to improve modeling of bond yields. In this paper two of such improvements are presented and discussed. The first improvement to be discussed is by Ang and Piazzesi (2003) who have found out that inclusion of macro variables to the affine term structure models provides a better fit empirically. The second improvement by Das (1998) also provides a better fitting term structure model by modeling the underlying state variable following a jump process.en_US
dc.description.statementofresponsibilityAksu, Gülşahen_US
dc.format.extentviii, 36 leaves, graphsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAffine Term Structure Modelsen_US
dc.subjectJump Diffusion Processesen_US
dc.subject.lccHG4651 .A57 2010en_US
dc.subject.lcshBonds--Valuation--Mathematical models.en_US
dc.subject.lcshInvestment analysis.en_US
dc.subject.lcshDiffusion processes.en_US
dc.titleContinuous time counterpart of vector auto regression of term structure dynamics with jump diffusion processesen_US
dc.typeThesisen_US
dc.departmentDepartment of Economicsen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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