A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries

Descripción del Articulo

Purpose – This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market. Design/method...

Descripción completa

Detalles Bibliográficos
Autores: Rossetti, Nara, Nagano, Marcelo Seido, Meirelles, Jorge Luis Faria
Formato: artículo
Fecha de Publicación:2017
Institución:Universidad ESAN
Repositorio:ESAN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.esan.edu.pe:20.500.12640/2605
Enlace del recurso:https://revistas.esan.edu.pe/index.php/jefas/article/view/128
https://hdl.handle.net/20.500.12640/2605
https://doi.org/10.1108/JEFAS-02-2017-0033
Nivel de acceso:acceso abierto
Materia:Volatility
Emerging countries
ARCH-GARCH models
Fixed income
Ingreso fijo
Volatilidad
Países emergentes
Modelos ARCH-GARCH
https://purl.org/pe-repo/ocde/ford#5.02.04
id ESAN_ff2455a44c5eb2a56e7997ed87237154
oai_identifier_str oai:repositorio.esan.edu.pe:20.500.12640/2605
network_acronym_str ESAN
network_name_str ESAN-Institucional
repository_id_str 4835
dc.title.en_EN.fl_str_mv A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
title A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
spellingShingle A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
Rossetti, Nara
Volatility
Emerging countries
ARCH-GARCH models
Fixed income
Ingreso fijo
Volatilidad
Países emergentes
Modelos ARCH-GARCH
https://purl.org/pe-repo/ocde/ford#5.02.04
title_short A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
title_full A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
title_fullStr A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
title_full_unstemmed A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
title_sort A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries
author Rossetti, Nara
author_facet Rossetti, Nara
Nagano, Marcelo Seido
Meirelles, Jorge Luis Faria
author_role author
author2 Nagano, Marcelo Seido
Meirelles, Jorge Luis Faria
author2_role author
author
dc.contributor.author.fl_str_mv Rossetti, Nara
Nagano, Marcelo Seido
Meirelles, Jorge Luis Faria
dc.subject.en_EN.fl_str_mv Volatility
Emerging countries
ARCH-GARCH models
Fixed income
topic Volatility
Emerging countries
ARCH-GARCH models
Fixed income
Ingreso fijo
Volatilidad
Países emergentes
Modelos ARCH-GARCH
https://purl.org/pe-repo/ocde/ford#5.02.04
dc.subject.es_ES.fl_str_mv Ingreso fijo
Volatilidad
Países emergentes
Modelos ARCH-GARCH
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#5.02.04
description Purpose – This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market. Design/methodology/approach – To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which of these processes were more efficient in capturing volatility of interest rates of each of the sample countries. Findings – The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events. Originality/value – It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2021-11-03T16:18:47Z
dc.date.available.none.fl_str_mv 2021-11-03T16:18:47Z
dc.date.issued.fl_str_mv 2017-06-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.other.none.fl_str_mv Artículo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.esan.edu.pe/index.php/jefas/article/view/128
dc.identifier.citation.none.fl_str_mv Rossetti, N., Nagano, M.S., & Meirelles, J.L.F. (2017). A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries. Journal of Economics, Finance and Administrative Science, 22(42), 99-128. https://doi.org/10.1108/JEFAS-02-2017-0033
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12640/2605
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1108/JEFAS-02-2017-0033
url https://revistas.esan.edu.pe/index.php/jefas/article/view/128
https://hdl.handle.net/20.500.12640/2605
https://doi.org/10.1108/JEFAS-02-2017-0033
identifier_str_mv Rossetti, N., Nagano, M.S., & Meirelles, J.L.F. (2017). A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries. Journal of Economics, Finance and Administrative Science, 22(42), 99-128. https://doi.org/10.1108/JEFAS-02-2017-0033
dc.language.none.fl_str_mv Inglés
dc.language.iso.none.fl_str_mv eng
language_invalid_str_mv Inglés
language eng
dc.relation.ispartof.none.fl_str_mv urn:issn:2218-0648
dc.relation.uri.none.fl_str_mv https://revistas.esan.edu.pe/index.php/jefas/article/view/128/105
dc.rights.en.fl_str_mv Attribution 4.0 International
dc.rights.es_ES.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.es_ES.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad ESAN. ESAN Ediciones
dc.publisher.country.none.fl_str_mv PE
publisher.none.fl_str_mv Universidad ESAN. ESAN Ediciones
dc.source.none.fl_str_mv reponame:ESAN-Institucional
instname:Universidad ESAN
instacron:ESAN
instname_str Universidad ESAN
instacron_str ESAN
institution ESAN
reponame_str ESAN-Institucional
collection ESAN-Institucional
bitstream.url.fl_str_mv https://repositorio.esan.edu.pe/bitstreams/77eb5a39-1e94-40a9-a315-509b984f32c1/download
https://repositorio.esan.edu.pe/bitstreams/e76e580c-6b77-413a-a4ac-84c48d9d1222/download
https://repositorio.esan.edu.pe/bitstreams/e1c8adc5-282c-4423-97df-e64138fdab26/download
https://repositorio.esan.edu.pe/bitstreams/66c113c2-3a39-4574-a4f0-63fd6a6f5e15/download
bitstream.checksum.fl_str_mv 0b3b58918313ec1b34477bb4ff530e80
aac39e8bf9fcd48745fa5015fd3cbde6
40e350fb9d8c4014a4051358fa1198dd
5c518bb5ad6a5788672024e09b688c51
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional ESAN
repository.mail.fl_str_mv repositorio@esan.edu.pe
_version_ 1843261686324133888
spelling Rossetti, NaraNagano, Marcelo SeidoMeirelles, Jorge Luis Faria2021-11-03T16:18:47Z2021-11-03T16:18:47Z2017-06-01https://revistas.esan.edu.pe/index.php/jefas/article/view/128Rossetti, N., Nagano, M.S., & Meirelles, J.L.F. (2017). A behavioral analysis of the volatility of interbank interest rates in developed and emerging countries. Journal of Economics, Finance and Administrative Science, 22(42), 99-128. https://doi.org/10.1108/JEFAS-02-2017-0033https://hdl.handle.net/20.500.12640/2605https://doi.org/10.1108/JEFAS-02-2017-0033Purpose – This paper aims to analyse the volatility of the fixed income market from 11 countries (Brazil, Russia, India, China, South Africa, Argentina, Chile, Mexico, USA, Germany and Japan) from January 2000 to December 2011 by examining the interbank interest rates from each market. Design/methodology/approach – To the volatility of interest rates returns, the study used models of auto-regressive conditional heteroscedasticity, autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), exponential generalized autoregressive conditional heteroscedasticity (EGARCH), threshold generalized autoregressive conditional heteroscedasticity (TGARCH) and periodic generalized autoregressive conditional heteroscedasticity (PGARCH), and a combination of these with autoregressive integrated moving average (ARIMA) models, checking which of these processes were more efficient in capturing volatility of interest rates of each of the sample countries. Findings – The results suggest that for most markets, studied volatility is best modelled by asymmetric GARCH processes – in this case the EGARCH – demonstrating that bad news leads to a higher increase in the volatility of these markets than good news. In addition, the causes of increased volatility seem to be more associated with events occurring internally in each country, as changes in macroeconomic policies, than the overall external events. Originality/value – It is expected that this study has contributed to a better understanding of the volatility of interest rates and the main factors affecting this market.Propósito – Este estudio analiza la volatilidad del mercado de renta fija de once países (Brasil, Rusia, India, China, Sudáfrica, Argentina, Chile, México, Estados Unidos, Alemania y Japón) de enero de 2000 a diciembre de 2011, mediante el examen de las tasas de interés interbancarias de cada mercado. Diseño/metodología/enfoque – Para la volatilidad de los retornos de las tasas de interés, se utilizaron modelos de heteroscedasticidad condicional autorregresiva: ARCH, GARCH, EGARCH, TGARCH y PGARCH, y una combinación de estos con modelos ARIMA, comprobando cuáles de los procesos eran más eficientes para capturar la volatilidad de interés de cada uno de los países de la muestra. Hallazgos – Los resultados sugieren que para la mayoría de los mercados estudiados la volatilidad es mejor modelada por procesos GARCH asimétricos —en este caso el EGARCH— demostrando que las malas noticias conducen a un mayor incremento en la volatilidad de estos mercados que las buenas noticias. Además, las causas de una mayor volatilidad parecen estar más asociadas a eventos que ocurren internamente en cada país, como cambios en las políticas macroeconómicas, que los eventos externos generales. Originalidad/valor – Se espera que este estudio contribuya a un mejor entendimiento de la volatilidad de las tasas de interés y de los principales factores que afectan a este mercado.application/pdfInglésengUniversidad ESAN. ESAN EdicionesPEurn:issn:2218-0648https://revistas.esan.edu.pe/index.php/jefas/article/view/128/105Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/VolatilityEmerging countriesARCH-GARCH modelsFixed incomeIngreso fijoVolatilidadPaíses emergentesModelos ARCH-GARCHhttps://purl.org/pe-repo/ocde/ford#5.02.04A behavioral analysis of the volatility of interbank interest rates in developed and emerging countriesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículoreponame:ESAN-Institucionalinstname:Universidad ESANinstacron:ESANJournal of Economics, Finance and Administrative Science128429922Acceso abiertoTHUMBNAIL42.jpg42.jpgimage/jpeg64641https://repositorio.esan.edu.pe/bitstreams/77eb5a39-1e94-40a9-a315-509b984f32c1/download0b3b58918313ec1b34477bb4ff530e80MD51falseAnonymousREADJEFAS-42-2017-99-128.pdf.jpgJEFAS-42-2017-99-128.pdf.jpgGenerated Thumbnailimage/jpeg5768https://repositorio.esan.edu.pe/bitstreams/e76e580c-6b77-413a-a4ac-84c48d9d1222/downloadaac39e8bf9fcd48745fa5015fd3cbde6MD54falseAnonymousREADORIGINALJEFAS-42-2017-99-128.pdfTexto completoapplication/pdf414403https://repositorio.esan.edu.pe/bitstreams/e1c8adc5-282c-4423-97df-e64138fdab26/download40e350fb9d8c4014a4051358fa1198ddMD52trueAnonymousREADTEXTJEFAS-42-2017-99-128.pdf.txtJEFAS-42-2017-99-128.pdf.txtExtracted texttext/plain78503https://repositorio.esan.edu.pe/bitstreams/66c113c2-3a39-4574-a4f0-63fd6a6f5e15/download5c518bb5ad6a5788672024e09b688c51MD53falseAnonymousREAD20.500.12640/2605oai:repositorio.esan.edu.pe:20.500.12640/26052025-07-09 09:30:10.713https://creativecommons.org/licenses/by/4.0/Attribution 4.0 Internationalopen.accesshttps://repositorio.esan.edu.peRepositorio Institucional ESANrepositorio@esan.edu.pe
score 13.955691
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).