Publicação
A new regression-based tail index estimator
| Resumo: | A new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided. |
|---|---|
| Autores principais: | Nicolau, João |
| Outros Autores: | Rodrigues, Paulo M. M. |
| Assunto: | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1865920832907247617 |
|---|---|
| author | Nicolau, João |
| author2 | Rodrigues, Paulo M. M. |
| author2_role | author |
| author_facet | Nicolau, João Nicolau, João Rodrigues, Paulo M. M. Rodrigues, Paulo M. M. |
| author_role | author |
| contributor_name_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Nicolau, João\"},{\"Person.name\":\"Rodrigues, Paulo M. M.\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Nicolau, João Rodrigues, Paulo M. M. |
| datacite.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-03-24T10:18:26Z |
| datacite.date.embargoed.fl_str_mv | 2023-03-24T10:18:26Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| datacite.titles.title.fl_str_mv | A new regression-based tail index estimator |
| dc.contributor.none.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Nicolau, João Rodrigues, Paulo M. M. |
| dc.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-03-24T10:18:26Z |
| dc.date.embargoed.fl_str_mv | 2023-03-24T10:18:26Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/27504 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Harvard College and the Massachusetts Institute of Technology |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| dc.title.fl_str_mv | A new regression-based tail index estimator |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | A new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/fb255e36-1eb0-41a2-b6c7-7aaff3647f7e/download |
| id | ul_c2e47296a97e24b5c8d8f577503ba0a5 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/27504 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/27504 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Nicolau, João Rodrigues, Paulo M. M. |
| publishDate | 2019 |
| publisher.none.fl_str_mv | Harvard College and the Massachusetts Institute of Technology |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engHarvard College and the Massachusetts Institute of Technologypt_PTA new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided.application/pdfpt_PTA new regression-based tail index estimatorNicolau, JoãoRodrigues, Paulo M. M.HostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptDOIIsPartOf10.1162/rest_a_007682023-03-24T10:18:26Z20192019-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/27504http://purl.org/coar/access_right/c_abf2open accessRegression-based ApproachPareto-type ModelMonte Carlo SimulationHeteroskcedasticity878191 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/fb255e36-1eb0-41a2-b6c7-7aaff3647f7e/download |
| spellingShingle | A new regression-based tail index estimator A new regression-based tail index estimator Nicolau, João Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity Nicolau, João Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| status | SINGLETON |
| subject.fl_str_mv | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| title | A new regression-based tail index estimator |
| title_full | A new regression-based tail index estimator |
| title_fullStr | A new regression-based tail index estimator A new regression-based tail index estimator |
| title_full_unstemmed | A new regression-based tail index estimator A new regression-based tail index estimator |
| title_short | A new regression-based tail index estimator |
| title_sort | A new regression-based tail index estimator |
| topic | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| topic_facet | Regression-based Approach Pareto-type Model Monte Carlo Simulation Heteroskcedasticity |
| url | http://hdl.handle.net/10400.5/27504 |
| visible | 1 |