Publicação
A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam
| Resumo: | The primary purpose of this report is to evaluate and improve the accuracy of Altman's Z-score model in financial distress prediction of listed companies in Vietnam. Identifying new cut off scores to the prediction models is necessary to adapt to the characteristics of the Vietnamese market. The study implements multiple discriminant analysis as a crucial methodology to calibrate the Z-score model with 51 forced delisted companies and 51 non-delisted companies. The Z new model achieves a one-year accuracy rate of 91.58% in forecasting financial distress for Vietnamese companies. The study shows that the superiority of the Altman Z-score model in financial distress prediction is not in the Z-score but in the methodology in which the model is built and put into practice. |
|---|---|
| Autores principais: | Tran, Duc Anh |
| Assunto: | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868982812815654912 |
|---|---|
| author | Tran, Duc Anh |
| author_facet | Tran, Duc Anh |
| author_role | author |
| contributor_name_str_mv | Demirci, Irem RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Tran, Duc Anh\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Demirci, Irem RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Tran, Duc Anh |
| datacite.date.Accepted.fl_str_mv | 2022-01-21T00:00:00Z |
| datacite.date.available.fl_str_mv | 2022-08-17T08:24:13Z |
| datacite.date.embargoed.fl_str_mv | 2022-08-17T08:24:13Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| datacite.titles.title.fl_str_mv | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| dc.contributor.none.fl_str_mv | Demirci, Irem RUN |
| dc.creator.none.fl_str_mv | Tran, Duc Anh |
| dc.date.Accepted.fl_str_mv | 2022-01-21T00:00:00Z |
| dc.date.available.fl_str_mv | 2022-08-17T08:24:13Z |
| dc.date.embargoed.fl_str_mv | 2022-08-17T08:24:13Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/143056 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| dc.title.fl_str_mv | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The primary purpose of this report is to evaluate and improve the accuracy of Altman's Z-score model in financial distress prediction of listed companies in Vietnam. Identifying new cut off scores to the prediction models is necessary to adapt to the characteristics of the Vietnamese market. The study implements multiple discriminant analysis as a crucial methodology to calibrate the Z-score model with 51 forced delisted companies and 51 non-delisted companies. The Z new model achieves a one-year accuracy rate of 91.58% in forecasting financial distress for Vietnamese companies. The study shows that the superiority of the Altman Z-score model in financial distress prediction is not in the Z-score but in the methodology in which the model is built and put into practice. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/f7d330a7-324b-49dd-a12d-1e62fe26be07/download |
| funder_facet_str_mv | FCT{{{_:::_}}}Fundação para a Ciência e a Tecnologia |
| funding.funder.alternateName_str_mv | FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | 6817 - DCRRNI ID |
| id | run_e3c77e46b77cd99b64d993f5ce971b21 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/143056 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/143056 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Tran, Duc Anh |
| publishDate | 2022 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
| repository_id_str | urn:repositoryAcronym:run |
| service_str_mv | urn:repositoryAcronym:run |
| spelling | engpt_PTThe primary purpose of this report is to evaluate and improve the accuracy of Altman's Z-score model in financial distress prediction of listed companies in Vietnam. Identifying new cut off scores to the prediction models is necessary to adapt to the characteristics of the Vietnamese market. The study implements multiple discriminant analysis as a crucial methodology to calibrate the Z-score model with 51 forced delisted companies and 51 non-delisted companies. The Z new model achieves a one-year accuracy rate of 91.58% in forecasting financial distress for Vietnamese companies. The study shows that the superiority of the Altman Z-score model in financial distress prediction is not in the Z-score but in the methodology in which the model is built and put into practice.application/pdfpt_PTA revision of Altman z-score model in financial distress prediction of listed companies in VietnamTran, Duc AnhDemirci, IremHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptURNurn:tid:2030209102022-08-17T08:24:13Z2022-01-212021-12-082022-01-21T00:00:00ZHandlehttp://hdl.handle.net/10362/143056http://purl.org/coar/access_right/c_abf2open accessFinancial distressAltman z score modelFinancial ratiosMultiple discriminant analysisPrediction modelVietnam699636 bytesFundação para a Ciência e a TecnologiaNova School of Business and Economics6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/f7d330a7-324b-49dd-a12d-1e62fe26be07/download |
| spellingShingle | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam Tran, Duc Anh Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| status | SINGLETON |
| subject.fl_str_mv | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| title | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| title_full | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| title_fullStr | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| title_full_unstemmed | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| title_short | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| title_sort | A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam |
| topic | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| topic_facet | Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam |
| url | http://hdl.handle.net/10362/143056 |
| visible | 1 |