An overview of modified semiparametric memory estimation methods

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dc.identifier.uri http://dx.doi.org/10.15488/4288
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/4322
dc.contributor.author Busch, Marie
dc.contributor.author Sibbertsen, Philipp
dc.date.accessioned 2019-01-11T08:57:39Z
dc.date.available 2019-01-11T08:57:39Z
dc.date.issued 2018
dc.identifier.citation Busch, M.; Sibbertsen, P.: An overview of modified semiparametric memory estimation methods. In: Econometrics 6 (2018), Nr. 1, 13. DOI: https://doi.org/10.3390/econometrics6010013
dc.description.abstract Several modified estimation methods of the memory parameter have been introduced in the past years. They aim to decrease the upward bias of the memory parameter in cases of low frequency contaminations or an additive noise component, especially in situations with a short-memory process being contaminated. In this paper, we provide an overview and compare the performance of nine semiparametric estimation methods. Among them are two standard methods, four modified approaches to account for low frequency contaminations and three procedures developed for perturbed fractional processes. We conduct an extensive Monte Carlo study for a variety of parameter constellations and several DGPs. Furthermore, an empirical application of the log-absolute return series of the S&P 500 shows that the estimation results combined with a long-memory test indicate a spurious long-memory process. eng
dc.language.iso eng
dc.publisher Basel : MDPI AG
dc.relation.ispartofseries Econometrics 6 (2018), Nr. 1
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Low frequency contamination eng
dc.subject Monte Carlo simulation eng
dc.subject Perturbation eng
dc.subject Semiparametric estimation eng
dc.subject Spurious long memory eng
dc.subject.ddc 330 | Wirtschaft ger
dc.title An overview of modified semiparametric memory estimation methods eng
dc.type article
dc.type Text
dc.relation.issn 2225-1146
dc.relation.doi https://doi.org/10.3390/econometrics6010013
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume 6
dc.bibliographicCitation.firstPage 13
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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