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Article: On a double-threshold autoregressive heteroscedastic time series model

TitleOn a double-threshold autoregressive heteroscedastic time series model
Authors
Issue Date1996
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://jae.wiley.com
Citation
Journal of Applied Econometrics, 1996, v. 11, p. 253-274 How to Cite?
AbstractTong's threshold models have been found useful in modelling nonlinearities in the conditional mean of a time series. The threshold model is extended to the so-called double-threshold ARCH(DTARCH) model, which can handle the situation where both the conditional mean and the conditional variance specifications are piecewise linear given previous information. Potential applications of such models include financial data with different (asymmetric) behaviour in a rising versus a falling market and business cycle modelling. Model identification, estimation and diagnostic checking techniques are developed. Maximum likelihood estimation can be achieved via an easy-to-use iteratively weighted least squares algorithm. Portmanteau-type statistics are also derived for checking model adequacy. An illustrative example demonstrates that asymmetric behaviour in the mean and the variance could be present in financial series and that the DTARCH model is capable of capturing these phenomena.
Persistent Identifierhttp://hdl.handle.net/10722/82994
ISSN
2015 Impact Factor: 1.872
2015 SCImago Journal Rankings: 2.253
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, CWen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:35:44Z-
dc.date.available2010-09-06T08:35:44Z-
dc.date.issued1996en_HK
dc.identifier.citationJournal of Applied Econometrics, 1996, v. 11, p. 253-274en_HK
dc.identifier.issn0883-7252en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82994-
dc.description.abstractTong's threshold models have been found useful in modelling nonlinearities in the conditional mean of a time series. The threshold model is extended to the so-called double-threshold ARCH(DTARCH) model, which can handle the situation where both the conditional mean and the conditional variance specifications are piecewise linear given previous information. Potential applications of such models include financial data with different (asymmetric) behaviour in a rising versus a falling market and business cycle modelling. Model identification, estimation and diagnostic checking techniques are developed. Maximum likelihood estimation can be achieved via an easy-to-use iteratively weighted least squares algorithm. Portmanteau-type statistics are also derived for checking model adequacy. An illustrative example demonstrates that asymmetric behaviour in the mean and the variance could be present in financial series and that the DTARCH model is capable of capturing these phenomena.-
dc.languageengen_HK
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://jae.wiley.comen_HK
dc.relation.ispartofJournal of Applied Econometricsen_HK
dc.rightsJournal of Applied Econometrics. Copyright © John Wiley & Sons Ltd.en_HK
dc.titleOn a double-threshold autoregressive heteroscedastic time series modelen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0883-7252&volume=11&spage=253&epage=274&date=1996&atitle=On+a+double-threshold+autoregressive+heteroscedastic+time+series+modelen_HK
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/(SICI)1099-1255(199605)11:3<253::AID-JAE393>3.0.CO;2-8-
dc.identifier.scopuseid_2-s2.0-21344443427-
dc.identifier.hkuros20041en_HK
dc.identifier.isiWOS:A1996UU80900002-

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