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/methodo...
| Autores: | , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2017 |
| Institución: | Universidad ESAN |
| Repositorio: | Revistas - Universidad ESAN |
| Lenguaje: | inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/128 |
| Enlace del recurso: | https://revistas.esan.edu.pe/index.php/jefas/article/view/128 |
| Nivel de acceso: | acceso abierto |
| Materia: | Volatility Emerging countries ARCH-GARCH models Fixed income |
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A behavioral analysis of the volatility of interbank interest rates in developed and emerging countriesRossetti, NaraSeido Nagano, MarceloFaria Meirelles, Jorge LuisVolatilityEmerging countriesARCH-GARCH modelsFixed incomePurpose. 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. Doi: https://doi.org/10.1108/JEFAS-02-2017-0033Universidad ESAN2017-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://revistas.esan.edu.pe/index.php/jefas/article/view/128Journal of Economics, Finance and Administrative Science; Vol. 22 No. 42 (2017): January - June; 99-128Journal of Economics, Finance and Administrative Science; Vol. 22 Núm. 42 (2017): January - June; 99-1282218-06482077-1886reponame:Revistas - Universidad ESANinstname:Universidad ESANinstacron:ESANenghttps://revistas.esan.edu.pe/index.php/jefas/article/view/128/105Copyright (c) 2021 Journal of Economics, Finance and Administrative Sciencehttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/1282021-06-20T00:02:13Z |
| dc.title.none.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 |
| 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 |
| dc.creator.none.fl_str_mv |
Rossetti, Nara Seido Nagano, Marcelo Faria Meirelles, Jorge Luis |
| author |
Rossetti, Nara |
| author_facet |
Rossetti, Nara Seido Nagano, Marcelo Faria Meirelles, Jorge Luis |
| author_role |
author |
| author2 |
Seido Nagano, Marcelo Faria Meirelles, Jorge Luis |
| author2_role |
author author |
| dc.subject.none.fl_str_mv |
Volatility Emerging countries ARCH-GARCH models Fixed income |
| topic |
Volatility Emerging countries ARCH-GARCH models Fixed income |
| 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. Doi: https://doi.org/10.1108/JEFAS-02-2017-0033 |
| publishDate |
2017 |
| dc.date.none.fl_str_mv |
2017-06-01 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistas.esan.edu.pe/index.php/jefas/article/view/128 |
| url |
https://revistas.esan.edu.pe/index.php/jefas/article/view/128 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
https://revistas.esan.edu.pe/index.php/jefas/article/view/128/105 |
| dc.rights.none.fl_str_mv |
Copyright (c) 2021 Journal of Economics, Finance and Administrative Science https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Copyright (c) 2021 Journal of Economics, Finance and Administrative Science https://creativecommons.org/licenses/by/4.0/ |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad ESAN |
| publisher.none.fl_str_mv |
Universidad ESAN |
| dc.source.none.fl_str_mv |
Journal of Economics, Finance and Administrative Science; Vol. 22 No. 42 (2017): January - June; 99-128 Journal of Economics, Finance and Administrative Science; Vol. 22 Núm. 42 (2017): January - June; 99-128 2218-0648 2077-1886 reponame:Revistas - Universidad ESAN instname:Universidad ESAN instacron:ESAN |
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Universidad ESAN |
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ESAN |
| institution |
ESAN |
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Revistas - Universidad ESAN |
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Revistas - Universidad ESAN |
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1853220128800374784 |
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12.680567 |
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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).