EconStor >
Queen Mary, University of London >
School of Economics and Finance, Queen Mary, University of London  >
Working Paper Series, School of Economics and Finance, Queen Mary, University of London  >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/55188
  

Full metadata record

DC FieldValueLanguage
dc.contributor.authorKapetanios, Georgeen_US
dc.contributor.authorPapailias, Fotisen_US
dc.date.accessioned2011-07-01en_US
dc.date.accessioned2012-02-09T14:07:12Z-
dc.date.available2012-02-09T14:07:12Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/55188-
dc.description.abstractWe consider the issue of Block Bootstrap methods in processes that exhibit strong dependence. The main difficulty is to transform the series in such way that implementation of these techniques can provide an accurate approximation to the true distribution of the test statistic under consideration. The bootstrap algorithm we suggest consists of the following operations: given xt ~ I(d0), 1) estimate the long memory parameter and obtain d, 2) difference the series d times, 3) times, 3) apply the block bootstrap on the above and finally, 4) cumulate the bootstrap sample times. Repetition of steps 3 and 4 for a sufficient number of times, results to a successful estimation of the distribution of the test statistic. Furthermore, we establish the asymptotic validity of this method. Its finite-sample properties are investigated via Monte Carlo experiments and the results indicate that it can be used as an alternative, and in most of the cases to be preferred than the Sieve AR bootstrap for fractional processes.en_US
dc.language.isoengen_US
dc.publisherQueen Mary, Univ. of London, School of Economics and Finance Londonen_US
dc.relation.ispartofseriesWorking Paper // School of Economics and Finance, Queen Mary, University of London 679en_US
dc.subject.jelC15en_US
dc.subject.jelC22en_US
dc.subject.jelC63en_US
dc.subject.ddc330en_US
dc.subject.keywordBlock Bootstrapen_US
dc.subject.keywordlong memoryen_US
dc.subject.keywordresamplingen_US
dc.subject.keywordstrong dependenceen_US
dc.titleBlock bootstrap and long memoryen_US
dc.typeWorking Paperen_US
dc.identifier.ppn663441889en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

Files in This Item:
File Description SizeFormat
663441889.pdf257.42 kBAdobe PDF
No. of Downloads: Counter Stats
Show simple item record
Download bibliographical data as: BibTeX

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