Machine learning Gaussian short rate

Detalhes bibliográficos
Autor(a) principal: Sousa, João Beleza Teixeira Seixas e
Data de Publicação: 2013
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/12230
Resumo: Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco
id RCAP_c74afb5ad74e32e370e5b79a2ba92f9a
oai_identifier_str oai:run.unl.pt:10362/12230
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Machine learning Gaussian short rateShort rateArbitrage free risk neutral measureGaussian processes for machine learningCalibrationZero coupon bondDissertação para obtenção do Grau de Doutor em Estatística e Gestão do RiscoThe main theme of this thesis is the calibration of a short rate model under the risk neutral measure. The problem of calibrating short rate models arises as most of the popular models have the drawback of not fitting prices observed in the market, in particular, those of the zero coupon bonds that define the current term structure of interest rates. This thesis proposes a risk neutral Gaussian short rate model based on Gaussian processes for machine learning regression using the Vasicek short rate model as prior. The proposed model fits not only the prices that define the current term structure observed in the market but also all past prices. The calibration is done using market observed zero coupon bond prices, exclusively. No other sources of information are needed. This thesis has two parts. The first part contains a set of self-contained finished papers, one already published, another accepted for publication and the others submitted for publication. The second part contains a set of self-contained unsubmitted papers. Although the fundamental work on papers in part two is finished as well, there are some extra work we want to include before submitting them for publication. Part I: - Machine learning Vasicek model calibration with Gaussian processes In this paper we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. We stress that the only prices needed for calibration are market observed zero coupon bond prices and that the parameters are directly obtained in the arbitrage free risk neutral measure. - One Factor Machine Learning Gaussian Short Rate In this paper we model the short rate, under the risk neutral measure, as a Gaussian process, conditioned on market observed zero coupon bonds log prices. The model is based on Gaussian processes for machine learning, using a single Vasicek factor as prior. All model parameters are learned directly under the risk neutral measure,using zero coupon bonds log prices only. The model supports observations of zero coupon bounds with distinct maturities limited to one observation per time instant. All the supported observations are automatically fitted.M2A/ISEL financing conference trips; ISEL - financing conference fees; ISEL/IPL the PROTEC scholarship; CMA/FCT/UNL - financing conference tripsFaculdade de Ciências e TecnologiaEsquível, Manuel L.Gaspar, RaquelRUNSousa, João Beleza Teixeira Seixas e2014-06-24T13:10:54Z20132013-01-01T00:00:00Zdoctoral thesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10362/12230TID:101429991enginfo: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:RCAAP2024-05-22T17:16:16Zoai:run.unl.pt:10362/12230Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T17:16:16Repositório 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 Machine learning Gaussian short rate
title Machine learning Gaussian short rate
spellingShingle Machine learning Gaussian short rate
Sousa, João Beleza Teixeira Seixas e
Short rate
Arbitrage free risk neutral measure
Gaussian processes for machine learning
Calibration
Zero coupon bond
title_short Machine learning Gaussian short rate
title_full Machine learning Gaussian short rate
title_fullStr Machine learning Gaussian short rate
title_full_unstemmed Machine learning Gaussian short rate
title_sort Machine learning Gaussian short rate
author Sousa, João Beleza Teixeira Seixas e
author_facet Sousa, João Beleza Teixeira Seixas e
author_role author
dc.contributor.none.fl_str_mv Esquível, Manuel L.
Gaspar, Raquel
RUN
dc.contributor.author.fl_str_mv Sousa, João Beleza Teixeira Seixas e
dc.subject.por.fl_str_mv Short rate
Arbitrage free risk neutral measure
Gaussian processes for machine learning
Calibration
Zero coupon bond
topic Short rate
Arbitrage free risk neutral measure
Gaussian processes for machine learning
Calibration
Zero coupon bond
description Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
2014-06-24T13:10:54Z
dc.type.driver.fl_str_mv doctoral thesis
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/12230
TID:101429991
url http://hdl.handle.net/10362/12230
identifier_str_mv TID:101429991
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.publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
publisher.none.fl_str_mv Faculdade de Ciências e Tecnologia
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 mluisa.alvim@gmail.com
_version_ 1817545514672979968

Registros relacionados