Development and testing of augmented distress prediction model: A comparative study on developed and emerging market
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/29145 https://doi.org/Ashraf, S., Félix, E.G.S. and Serrasqueiro, Z., 2020. Development and testing of augmented distress prediction model: A comparative study on developed and emerging market. Journal of Multinational Financial Management, 57-58, 100659 https://doi.org/10.1016/j.mulfin.2020.100659 https://doi.org/10.1016/j.mulfin.2020.100659 |
Resumo: | This study presents a financial distress (FD) prediction model that utilizes accounting, market-based, and financial reporting quality (FRQ) measures. We use a panel logit framework to analyze data for developed market firms from the UK and emerging market firms from Pakistan during the period 2001-2015. Obscured portions of financial reports, such as that created by management tactics employing income smoothing, can be measured with FRQ proxies. Our results find that such FRQ measures have significant influence on the accuracy of distress prediction modeling, in both the UK and Pakistani markets. Further, we validate the performance of our models through a fully non-linear classifier known as random forest methodology. Our robustness checks reveal that the predictive accuracy of our model remains high during different tranches of the business cycle and across different econometric techniques. |
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Development and testing of augmented distress prediction model: A comparative study on developed and emerging marketFinancial distresspanel logit analysisrandom forest methodologyfinancial reporting qualityearning managementThis study presents a financial distress (FD) prediction model that utilizes accounting, market-based, and financial reporting quality (FRQ) measures. We use a panel logit framework to analyze data for developed market firms from the UK and emerging market firms from Pakistan during the period 2001-2015. Obscured portions of financial reports, such as that created by management tactics employing income smoothing, can be measured with FRQ proxies. Our results find that such FRQ measures have significant influence on the accuracy of distress prediction modeling, in both the UK and Pakistani markets. Further, we validate the performance of our models through a fully non-linear classifier known as random forest methodology. Our robustness checks reveal that the predictive accuracy of our model remains high during different tranches of the business cycle and across different econometric techniques.Journal of Multinational Financial Management2021-02-18T11:15:24Z2021-02-182020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/29145https://doi.org/Ashraf, S., Félix, E.G.S. and Serrasqueiro, Z., 2020. Development and testing of augmented distress prediction model: A comparative study on developed and emerging market. Journal of Multinational Financial Management, 57-58, 100659 https://doi.org/10.1016/j.mulfin.2020.100659http://hdl.handle.net/10174/29145https://doi.org/10.1016/j.mulfin.2020.100659engdrsumairaa@gmail.comefelix@uevora.ptzelia@ubi.pt256Ashraf, SumairaFélix, Elisabete G. S.Serrasqueiro, Zéliainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:26:02Zoai:dspace.uevora.pt:10174/29145Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:18:52.836009Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
title |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
spellingShingle |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market Ashraf, Sumaira Financial distress panel logit analysis random forest methodology financial reporting quality earning management |
title_short |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
title_full |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
title_fullStr |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
title_full_unstemmed |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
title_sort |
Development and testing of augmented distress prediction model: A comparative study on developed and emerging market |
author |
Ashraf, Sumaira |
author_facet |
Ashraf, Sumaira Félix, Elisabete G. S. Serrasqueiro, Zélia |
author_role |
author |
author2 |
Félix, Elisabete G. S. Serrasqueiro, Zélia |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ashraf, Sumaira Félix, Elisabete G. S. Serrasqueiro, Zélia |
dc.subject.por.fl_str_mv |
Financial distress panel logit analysis random forest methodology financial reporting quality earning management |
topic |
Financial distress panel logit analysis random forest methodology financial reporting quality earning management |
description |
This study presents a financial distress (FD) prediction model that utilizes accounting, market-based, and financial reporting quality (FRQ) measures. We use a panel logit framework to analyze data for developed market firms from the UK and emerging market firms from Pakistan during the period 2001-2015. Obscured portions of financial reports, such as that created by management tactics employing income smoothing, can be measured with FRQ proxies. Our results find that such FRQ measures have significant influence on the accuracy of distress prediction modeling, in both the UK and Pakistani markets. Further, we validate the performance of our models through a fully non-linear classifier known as random forest methodology. Our robustness checks reveal that the predictive accuracy of our model remains high during different tranches of the business cycle and across different econometric techniques. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01T00:00:00Z 2021-02-18T11:15:24Z 2021-02-18 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/29145 https://doi.org/Ashraf, S., Félix, E.G.S. and Serrasqueiro, Z., 2020. Development and testing of augmented distress prediction model: A comparative study on developed and emerging market. Journal of Multinational Financial Management, 57-58, 100659 https://doi.org/10.1016/j.mulfin.2020.100659 http://hdl.handle.net/10174/29145 https://doi.org/10.1016/j.mulfin.2020.100659 |
url |
http://hdl.handle.net/10174/29145 https://doi.org/Ashraf, S., Félix, E.G.S. and Serrasqueiro, Z., 2020. Development and testing of augmented distress prediction model: A comparative study on developed and emerging market. Journal of Multinational Financial Management, 57-58, 100659 https://doi.org/10.1016/j.mulfin.2020.100659 https://doi.org/10.1016/j.mulfin.2020.100659 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
drsumairaa@gmail.com efelix@uevora.pt zelia@ubi.pt 256 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Journal of Multinational Financial Management |
publisher.none.fl_str_mv |
Journal of Multinational Financial Management |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136670636834816 |