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dc.contributor.authorNarayanasamy, Arun Prasathen_US
dc.date.accessioned2012-07-25T19:08:07Z
dc.date.available2012-07-25T19:08:07Z
dc.date.issued2012-07-25
dc.date.submittedJanuary 2012en_US
dc.identifier.otherDISS-11760en_US
dc.identifier.urihttp://hdl.handle.net/10106/11032
dc.description.abstractMost research on volatility spillovers across countries and various asset class returns model volatility as conditional variance and assume a linear relationship in spillovers. The risk measured as conditional variance is modeled as a function of own past innovations and own past conditional variances and fails to include lagged conditional variances from other assets. In this dissertation, for a bivariate set up, I estimate the conditional variance of the second country either as a GARCH (1, 1) or DCC (1, 1) type process. Using the estimated conditional variances, the non-linear or threshold parameter is computed by maximizing the log likelihood function and is included in the second stage estimation of spillovers in the newly specified extended conditional variance equation for the first country which allows for conditional variances from other assets to affect it. While it appears that spillovers and threshold effects should be positive I provide evidence of positive direct spillovers and negative indirect threshold effects across markets within three different asset classes.en_US
dc.description.sponsorshipSmallwood, Aaronen_US
dc.language.isoenen_US
dc.publisherFinance & Real Estateen_US
dc.titleThreshold Effects In Volatility Spillovers: The Case Of Equity, Bond And Foreign Exchange Marketsen_US
dc.typePh.D.en_US
dc.contributor.committeeChairSmallwood, Aaronen_US
dc.degree.departmentFinance & Real Estateen_US
dc.degree.disciplineFinance & Real Estateen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.leveldoctoralen_US
dc.degree.namePh.D.en_US


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