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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/100442
Ver los metadatos del registro completo
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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 |
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1842268959052660736 |
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13.13397 |