Credit risk modelling using multi-state markov models

Detalhes bibliográficos
Autor(a) principal: Santos, João Paulo Nogueira
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/63689
Resumo: A Dissertation as a partial requirement to obtain the degree of Master in Statistics and Information Management, specialization in Risk Analysis and Management
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spelling Credit risk modelling using multi-state markov modelsProbability of defaultMortgage loansMulti-state Markov ModelCredit RiskMsmA Dissertation as a partial requirement to obtain the degree of Master in Statistics and Information Management, specialization in Risk Analysis and ManagementThis paper is devoted to credit risk modelling issues concerning mortgage commercial loans. Mortgage loans are one of the most popular type of loans provided by credit institutions. Like in the case of other loans, the main concern of institutions providing this type of product is a potential inability to recover the amount assigned to their clients (credit risk). In order to prevent possible losses for credit institutions resulting from clients entering in default, it is therefore crucial to study the behaviour of risky clients. This issue can be addressed through several models, namely through the multi-state Markov model, despite it constituting a more unusual approach in the context of dealing with credit risk modelling. The multi-state Markov model is a useful way of describing a process in which an individual moves through a series of states (finite number) in continuous time. By fitting this model to the loans of risky clients, it is possible to estimate the mean sojourn time in each state before a transition occurs, as well as the transition probabilities between the different states assumed by the contracts, therefore providing a relevant modelling framework for event history data. The present work relies upon 2008-13 databases from one of the biggest American companies that act in the secondary mortgage market, the Fannie Mae. Results show that with the application of the multi-state Markov model, contracts signed during 2013 are more propitious to a scenario of recovery when compared to those referring to the year 2008.Bravo, Jorge Miguel VenturaRUNSantos, João Paulo Nogueira2019-03-18T16:33:31Z2018-03-282018-03-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/63689TID:202196178enginfo: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:RCAAP2024-03-11T04:30:13Zoai:run.unl.pt:10362/63689Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:33:58.289625Repositório 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 Credit risk modelling using multi-state markov models
title Credit risk modelling using multi-state markov models
spellingShingle Credit risk modelling using multi-state markov models
Santos, João Paulo Nogueira
Probability of default
Mortgage loans
Multi-state Markov Model
Credit Risk
Msm
title_short Credit risk modelling using multi-state markov models
title_full Credit risk modelling using multi-state markov models
title_fullStr Credit risk modelling using multi-state markov models
title_full_unstemmed Credit risk modelling using multi-state markov models
title_sort Credit risk modelling using multi-state markov models
author Santos, João Paulo Nogueira
author_facet Santos, João Paulo Nogueira
author_role author
dc.contributor.none.fl_str_mv Bravo, Jorge Miguel Ventura
RUN
dc.contributor.author.fl_str_mv Santos, João Paulo Nogueira
dc.subject.por.fl_str_mv Probability of default
Mortgage loans
Multi-state Markov Model
Credit Risk
Msm
topic Probability of default
Mortgage loans
Multi-state Markov Model
Credit Risk
Msm
description A Dissertation as a partial requirement to obtain the degree of Master in Statistics and Information Management, specialization in Risk Analysis and Management
publishDate 2018
dc.date.none.fl_str_mv 2018-03-28
2018-03-28T00:00:00Z
2019-03-18T16:33:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/63689
TID:202196178
url http://hdl.handle.net/10362/63689
identifier_str_mv TID:202196178
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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
instname_str 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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