Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62815 
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBlake, Andrew P.en
dc.contributor.authorKapetanios, Georgeen
dc.date.accessioned2012-09-20T12:59:13Z-
dc.date.available2012-09-20T12:59:13Z-
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10419/62815-
dc.description.abstractTests of ARCH are a routine diagnostic in empirical econometric and financial analysis. However, it is well known that misspecification of the conditional mean may lead to spurious rejections of the null hypothesis of no ARCH. Nonlinearity is a prime example of this phenomenon. There is little work on the extent of the effect of neglected nonlinearity on the properties of ARCH tests. This paper provides some such evidence and also new ARCH testing procedures that are robust to the presence of neglected nonlinearity. Monte Carlo evidence shows that the problem is serious and that the new methods alleviate this problem to a very large extent.en
dc.language.isoengen
dc.publisher|aQueen Mary University of London, Department of Economics |cLondonen
dc.relation.ispartofseries|aWorking Paper |x496en
dc.subject.jelC12en
dc.subject.jelC22en
dc.subject.jelC45en
dc.subject.ddc330en
dc.subject.keywordNonlinearity, ARCH, Neural networksen
dc.subject.stwARCH-Modellen
dc.subject.stwNeuronale Netzeen
dc.subject.stwNichtlineares Verfahrenen
dc.titleTesting for ARCH in the presence of nonlinearity of unknow form in the conditional mean-
dc.typeWorking Paperen
dc.identifier.ppn377046299en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

Files in This Item:
File
Size
192.34 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.