dc.contributor.author | Narayanasamy, Arun Prasath | en_US |
dc.date.accessioned | 2012-07-25T19:08:07Z | |
dc.date.available | 2012-07-25T19:08:07Z | |
dc.date.issued | 2012-07-25 | |
dc.date.submitted | January 2012 | en_US |
dc.identifier.other | DISS-11760 | en_US |
dc.identifier.uri | http://hdl.handle.net/10106/11032 | |
dc.description.abstract | Most 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.sponsorship | Smallwood, Aaron | en_US |
dc.language.iso | en | en_US |
dc.publisher | Finance & Real Estate | en_US |
dc.title | Threshold Effects In Volatility Spillovers: The Case Of Equity, Bond And Foreign Exchange Markets | en_US |
dc.type | Ph.D. | en_US |
dc.contributor.committeeChair | Smallwood, Aaron | en_US |
dc.degree.department | Finance & Real Estate | en_US |
dc.degree.discipline | Finance & Real Estate | en_US |
dc.degree.grantor | University of Texas at Arlington | en_US |
dc.degree.level | doctoral | en_US |
dc.degree.name | Ph.D. | en_US |