Credit default swap (CDS) prediction model & trading strategy

Detalhes bibliográficos
Autor(a) principal: Dutra, Tiago Mota
Data de Publicação: 2015
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/15345
Resumo: This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.
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spelling Credit default swap (CDS) prediction model & trading strategyCredit default swapEconometric prediction modelQuantile regressionTrading strategyThis project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.UNL - NSBEPereira, João PedroRUNDutra, Tiago Mota2015-08-25T09:47:09Z2015-012015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/15345TID:201473437enginfo: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:RCAAP2024-03-11T03:51:15Zoai:run.unl.pt:10362/15345Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:22:27.843917Repositório 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 default swap (CDS) prediction model & trading strategy
title Credit default swap (CDS) prediction model & trading strategy
spellingShingle Credit default swap (CDS) prediction model & trading strategy
Dutra, Tiago Mota
Credit default swap
Econometric prediction model
Quantile regression
Trading strategy
title_short Credit default swap (CDS) prediction model & trading strategy
title_full Credit default swap (CDS) prediction model & trading strategy
title_fullStr Credit default swap (CDS) prediction model & trading strategy
title_full_unstemmed Credit default swap (CDS) prediction model & trading strategy
title_sort Credit default swap (CDS) prediction model & trading strategy
author Dutra, Tiago Mota
author_facet Dutra, Tiago Mota
author_role author
dc.contributor.none.fl_str_mv Pereira, João Pedro
RUN
dc.contributor.author.fl_str_mv Dutra, Tiago Mota
dc.subject.por.fl_str_mv Credit default swap
Econometric prediction model
Quantile regression
Trading strategy
topic Credit default swap
Econometric prediction model
Quantile regression
Trading strategy
description This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-25T09:47:09Z
2015-01
2015-01-01T00:00:00Z
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/10362/15345
TID:201473437
url http://hdl.handle.net/10362/15345
identifier_str_mv TID:201473437
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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