Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model

Autores
Hevia, Constantino; Gonzalez Rozada, Martin; Sola, Martin; Spagnolo, Walter Fabio
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We estimate versions of the Nelson-Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non-arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single-regime Nelson and Siegel model and other standard empirical models of the yield curve.
Fil: Hevia, Constantino. World Bank; Estados Unidos. Universidad Torcuato Di Tella; Argentina
Fil: Gonzalez Rozada, Martin. Universidad Torcuato Di Tella; Argentina
Fil: Sola, Martin. Birkbeck College; Reino Unido. Universidad Torcuato Di Tella; Argentina
Fil: Spagnolo, Walter Fabio. Brunel University; Reino Unido
Materia
Yield Curve
Term structure of interest rates
Markov regime switching
Maxi- mum likelihood
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/100442

id CONICETDig_a25fb6b9d6bfca116ad6463fc147e2af
oai_identifier_str oai:ri.conicet.gov.ar:11336/100442
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel ModelHevia, ConstantinoGonzalez Rozada, MartinSola, MartinSpagnolo, Walter FabioYield CurveTerm structure of interest ratesMarkov regime switchingMaxi- mum likelihoodhttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5We estimate versions of the Nelson-Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non-arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single-regime Nelson and Siegel model and other standard empirical models of the yield curve.Fil: Hevia, Constantino. World Bank; Estados Unidos. Universidad Torcuato Di Tella; ArgentinaFil: Gonzalez Rozada, Martin. Universidad Torcuato Di Tella; ArgentinaFil: Sola, Martin. Birkbeck College; Reino Unido. Universidad Torcuato Di Tella; ArgentinaFil: Spagnolo, Walter Fabio. Brunel University; Reino UnidoJohn Wiley & Sons Ltd2015-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/100442Hevia, Constantino; Gonzalez Rozada, Martin; Sola, Martin; Spagnolo, Walter Fabio; Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model; John Wiley & Sons Ltd; Journal of Applied Econometrics; 30; 6; 9-2015; 987-10091099-1255CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/jae.2399info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/jae.2399info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:49:11Zoai:ri.conicet.gov.ar:11336/100442instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:49:12.1CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
title Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
spellingShingle Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
Hevia, Constantino
Yield Curve
Term structure of interest rates
Markov regime switching
Maxi- mum likelihood
title_short Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
title_full Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
title_fullStr Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
title_full_unstemmed Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
title_sort Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model
dc.creator.none.fl_str_mv Hevia, Constantino
Gonzalez Rozada, Martin
Sola, Martin
Spagnolo, Walter Fabio
author Hevia, Constantino
author_facet Hevia, Constantino
Gonzalez Rozada, Martin
Sola, Martin
Spagnolo, Walter Fabio
author_role author
author2 Gonzalez Rozada, Martin
Sola, Martin
Spagnolo, Walter Fabio
author2_role author
author
author
dc.subject.none.fl_str_mv Yield Curve
Term structure of interest rates
Markov regime switching
Maxi- mum likelihood
topic Yield Curve
Term structure of interest rates
Markov regime switching
Maxi- mum likelihood
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv We estimate versions of the Nelson-Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non-arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single-regime Nelson and Siegel model and other standard empirical models of the yield curve.
Fil: Hevia, Constantino. World Bank; Estados Unidos. Universidad Torcuato Di Tella; Argentina
Fil: Gonzalez Rozada, Martin. Universidad Torcuato Di Tella; Argentina
Fil: Sola, Martin. Birkbeck College; Reino Unido. Universidad Torcuato Di Tella; Argentina
Fil: Spagnolo, Walter Fabio. Brunel University; Reino Unido
description We estimate versions of the Nelson-Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non-arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single-regime Nelson and Siegel model and other standard empirical models of the yield curve.
publishDate 2015
dc.date.none.fl_str_mv 2015-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/100442
Hevia, Constantino; Gonzalez Rozada, Martin; Sola, Martin; Spagnolo, Walter Fabio; Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model; John Wiley & Sons Ltd; Journal of Applied Econometrics; 30; 6; 9-2015; 987-1009
1099-1255
CONICET Digital
CONICET
url http://hdl.handle.net/11336/100442
identifier_str_mv Hevia, Constantino; Gonzalez Rozada, Martin; Sola, Martin; Spagnolo, Walter Fabio; Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model; John Wiley & Sons Ltd; Journal of Applied Econometrics; 30; 6; 9-2015; 987-1009
1099-1255
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/jae.2399
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/jae.2399
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Ltd
publisher.none.fl_str_mv John Wiley & Sons Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842268959052660736
score 13.13397