Forecasting the term structure of the Euro Market using Principal Component Analysis

dc.contributor.authorDauwe, Alexander
dc.contributor.authorMoura, Marcelo L.
dc.coverage.cidadeSão Paulopt_BR
dc.coverage.paisBrasilpt_BR
dc.creatorDauwe, Alexander
dc.creatorMoura, Marcelo L.
dc.date.accessioned2023-07-17T19:38:56Z
dc.date.available2023-07-17T19:38:56Z
dc.date.issued2011
dc.description.otherWe forecast the monthly Euro Interest Rate Swap Curve with an autoregressive principal component model. We compare its predictability accuracy against the Diebold and Li’s dynamic Nelson Siegel, the auto-regressive direct regression of the yield levels and the random walk model. After a robust set of specifications and regression windows, we conclude that our proposed model achieve forecasts that significantly outperform the competitor models, mainly for short run horizons.pt_BR
dc.format.extent21 p.pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.issueBEWP 135/2011
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/5839
dc.language.isoInglêspt_BR
dc.publisherInsperpt_BR
dc.publisherIBMEC São Paulopt_BR
dc.relation.ispartofseriesInsper Working Paperpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DO USUÁRIO VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.subject.keywordsTerm structure forecastingpt_BR
dc.subject.keywordsPrincipal component modelpt_BR
dc.subject.keywordsNelson-Siegel modept_BR
dc.subject.keywordsAR(1)pt_BR
dc.subject.keywordsVAR(1)pt_BR
dc.subject.keywordsModel selectionpt_BR
dc.subject.keywordsOut-of-sample forecasting evaluationspt_BR
dc.titleForecasting the term structure of the Euro Market using Principal Component Analysispt_BR
dc.typeworking paper
dspace.entity.typePublication
local.typeWorking Paperpt_BR

Arquivos

Pacote original

Agora exibindo 1 - 1 de 1
N/D
Nome:
BEWP_135_2011_Forecasting_the_term_structure_of_the_euro_market_using_principal_component_analysis_TC.pdf
Tamanho:
1.26 MB
Formato:
Adobe Portable Document Format