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Article: The ZD-GARCH model: A new way to study heteroscedasticity

TitleThe ZD-GARCH model: A new way to study heteroscedasticity
Authors
KeywordsConditional heteroscedasticity
GARCH model
Generalized quasi-maximum likelihood estimator
Heteroscedasticity
Portmanteau test
Stability test
Top Lyapunov exponent
Zero-drift GARCH model
Issue Date2018
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom
Citation
Journal of Econometrics, 2018, v. 202 n. 1, p. 1-17 How to Cite?
AbstractThis paper proposes a first-order zero-drift GARCH (ZD-GARCH(1, 1)) model to study conditional heteroscedasticity and heteroscedasticity together. Unlike the classical GARCH model, the ZD-GARCH(1, 1) model is always non-stationary regardless of the sign of the Lyapunov exponent γ0, but interestingly it is stable with its sample path oscillating randomly between zero and infinity over time when γ0=0. Furthermore, this paper studies the generalized quasi-maximum likelihood estimator (GQMLE) of the ZD-GARCH(1, 1) model, and establishes its strong consistency and asymptotic normality. Based on the GQMLE, an estimator for γ0, a t-test for stability, a unit root test for the absence of the drift term, and a portmanteau test for model checking are all constructed. Simulation studies are carried out to assess the finite sample performance of the proposed estimators and tests. Applications demonstrate that a stable ZD-GARCH(1, 1) model is more appropriate than a non-stationary GARCH(1, 1) model in fitting the KV-A stock returns in Francq and Zakoïan (2012).
Persistent Identifierhttp://hdl.handle.net/10722/266459
ISSN
2017 Impact Factor: 1.632
2015 SCImago Journal Rankings: 3.781
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, D-
dc.contributor.authorZhang, X-
dc.contributor.authorZhu, K-
dc.contributor.authorLing, S-
dc.date.accessioned2019-01-18T08:20:04Z-
dc.date.available2019-01-18T08:20:04Z-
dc.date.issued2018-
dc.identifier.citationJournal of Econometrics, 2018, v. 202 n. 1, p. 1-17-
dc.identifier.issn0304-4076-
dc.identifier.urihttp://hdl.handle.net/10722/266459-
dc.description.abstractThis paper proposes a first-order zero-drift GARCH (ZD-GARCH(1, 1)) model to study conditional heteroscedasticity and heteroscedasticity together. Unlike the classical GARCH model, the ZD-GARCH(1, 1) model is always non-stationary regardless of the sign of the Lyapunov exponent γ0, but interestingly it is stable with its sample path oscillating randomly between zero and infinity over time when γ0=0. Furthermore, this paper studies the generalized quasi-maximum likelihood estimator (GQMLE) of the ZD-GARCH(1, 1) model, and establishes its strong consistency and asymptotic normality. Based on the GQMLE, an estimator for γ0, a t-test for stability, a unit root test for the absence of the drift term, and a portmanteau test for model checking are all constructed. Simulation studies are carried out to assess the finite sample performance of the proposed estimators and tests. Applications demonstrate that a stable ZD-GARCH(1, 1) model is more appropriate than a non-stationary GARCH(1, 1) model in fitting the KV-A stock returns in Francq and Zakoïan (2012).-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom-
dc.relation.ispartofJournal of Econometrics-
dc.subjectConditional heteroscedasticity-
dc.subjectGARCH model-
dc.subjectGeneralized quasi-maximum likelihood estimator-
dc.subjectHeteroscedasticity-
dc.subjectPortmanteau test-
dc.subjectStability test-
dc.subjectTop Lyapunov exponent-
dc.subjectZero-drift GARCH model-
dc.titleThe ZD-GARCH model: A new way to study heteroscedasticity-
dc.typeArticle-
dc.identifier.emailZhu, K: mazhuke@hku.hk-
dc.identifier.authorityZhu, K=rp02199-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jeconom.2017.09.003-
dc.identifier.scopuseid_2-s2.0-85032944627-
dc.identifier.hkuros296557-
dc.identifier.volume202-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage17-
dc.identifier.isiWOS:000418106300001-
dc.publisher.placeNetherlands-

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