Non-parametric analysis of serial dependence in time series using ordinal patterns

A list of new tests for serial dependence based on ordinal patterns are provided. These new methods rely exclusively on the order structure of the data sets. Hence, the novel tests are stable under monotone transformations of the time series and robust against small perturbations or measurement erro...

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Detalles Bibliográficos
Autores: Weiß, Christian H., Ruiz Marín, Manuel, Keller, Karsten, Matilla García, Mariano
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Nacional de Educación a Distancia
Repositorio:e-spacio. Repositorio Institucional de la UNED
Idioma:inglés
OAI Identifier:oai:e-spacio.uned.es:20.500.14468/24622
Acceso en línea:https://hdl.handle.net/20.500.14468/24622
Access Level:acceso abierto
Palabra clave:53 Ciencias Económicas
non-parametric tests
ordinal patterns
ordinal time series
real-valued time series
serial dependence
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spelling Non-parametric analysis of serial dependence in time series using ordinal patternsWeiß, Christian H.Ruiz Marín, ManuelKeller, KarstenMatilla García, Mariano53 Ciencias Económicasnon-parametric testsordinal patternsordinal time seriesreal-valued time seriesserial dependenceA list of new tests for serial dependence based on ordinal patterns are provided. These new methods rely exclusively on the order structure of the data sets. Hence, the novel tests are stable under monotone transformations of the time series and robust against small perturbations or measurement errors. The standard asymptotic distributions are given, and their finite sample behavior under linear and non-linear departures from the null of independence are studied. Moreover, it is proved that under mild conditions, any ordinal-pattern-based test is nuisance free, which is appealing for modelling, as these tests can eventually be used as misspecification tests. This property is also analyzed for finite samples and illustrated through an empirical application. Much of the discussion is based on a detailed combinatorial analysis of ordinal pattern probabilitiesElseviere-Spacio UNED20242024-12-0220222022-04-0120222022-04-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14468/24622reponame:e-spacio. Repositorio Institucional de la UNEDinstname:Universidad Nacional de Educación a DistanciaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.esoai:e-spacio.uned.es:20.500.14468/246222026-06-06T12:38:31Z
dc.title.none.fl_str_mv Non-parametric analysis of serial dependence in time series using ordinal patterns
title Non-parametric analysis of serial dependence in time series using ordinal patterns
spellingShingle Non-parametric analysis of serial dependence in time series using ordinal patterns
Weiß, Christian H.
53 Ciencias Económicas
non-parametric tests
ordinal patterns
ordinal time series
real-valued time series
serial dependence
title_short Non-parametric analysis of serial dependence in time series using ordinal patterns
title_full Non-parametric analysis of serial dependence in time series using ordinal patterns
title_fullStr Non-parametric analysis of serial dependence in time series using ordinal patterns
title_full_unstemmed Non-parametric analysis of serial dependence in time series using ordinal patterns
title_sort Non-parametric analysis of serial dependence in time series using ordinal patterns
dc.creator.none.fl_str_mv Weiß, Christian H.
Ruiz Marín, Manuel
Keller, Karsten
Matilla García, Mariano
author Weiß, Christian H.
author_facet Weiß, Christian H.
Ruiz Marín, Manuel
Keller, Karsten
Matilla García, Mariano
author_role author
author2 Ruiz Marín, Manuel
Keller, Karsten
Matilla García, Mariano
author2_role author
author
author
dc.contributor.none.fl_str_mv e-Spacio UNED
dc.subject.none.fl_str_mv 53 Ciencias Económicas
non-parametric tests
ordinal patterns
ordinal time series
real-valued time series
serial dependence
topic 53 Ciencias Económicas
non-parametric tests
ordinal patterns
ordinal time series
real-valued time series
serial dependence
description A list of new tests for serial dependence based on ordinal patterns are provided. These new methods rely exclusively on the order structure of the data sets. Hence, the novel tests are stable under monotone transformations of the time series and robust against small perturbations or measurement errors. The standard asymptotic distributions are given, and their finite sample behavior under linear and non-linear departures from the null of independence are studied. Moreover, it is proved that under mild conditions, any ordinal-pattern-based test is nuisance free, which is appealing for modelling, as these tests can eventually be used as misspecification tests. This property is also analyzed for finite samples and illustrated through an empirical application. Much of the discussion is based on a detailed combinatorial analysis of ordinal pattern probabilities
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-04-01
2022
2022-04-01
2024
2024-12-02
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14468/24622
url https://hdl.handle.net/20.500.14468/24622
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:e-spacio. Repositorio Institucional de la UNED
instname:Universidad Nacional de Educación a Distancia
instname_str Universidad Nacional de Educación a Distancia
reponame_str e-spacio. Repositorio Institucional de la UNED
collection e-spacio. Repositorio Institucional de la UNED
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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