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Asymptotic Normality for Threshold-Asymmetric GARCH Processes of Non-Stationary Cases
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 박진아 | - |
| dc.contributor.author | 황선영 | - |
| dc.date.available | 2021-02-22T13:31:51Z | - |
| dc.date.issued | 2011-07 | - |
| dc.identifier.issn | 2287-7843 | - |
| dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/12909 | - |
| dc.description.abstract | This article is concerned with a class of threshold-asymmetric GARCH models both for stationary case and for non-stationary case. We investigate large sample properties of estimators from QML(quasi-maximum likelihood) and QL(quasilikelihood) methods. Asymptotic distributions are derived and it is interesting to note for non-stationary case that both QML and QL give asymptotic normal distributions. | - |
| dc.format.extent | 7 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | 한국통계학회 | - |
| dc.title | Asymptotic Normality for Threshold-Asymmetric GARCH Processes of Non-Stationary Cases | - |
| dc.type | Article | - |
| dc.publisher.location | South Korea | - |
| dc.identifier.bibliographicCitation | Communications for Statistical Applications and Methods, v.18, no.4, pp 477 - 483 | - |
| dc.citation.title | Communications for Statistical Applications and Methods | - |
| dc.citation.volume | 18 | - |
| dc.citation.number | 4 | - |
| dc.citation.startPage | 477 | - |
| dc.citation.endPage | 483 | - |
| dc.identifier.kciid | ART001574333 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Quasilikelihood | - |
| dc.subject.keywordAuthor | quasi-maximum likelihood | - |
| dc.subject.keywordAuthor | non-stationary | - |
| dc.subject.keywordAuthor | threshold | - |
| dc.identifier.url | http://kiss.kstudy.com/thesis/thesis-view.asp?key=2930641 | - |
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