Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets
Descripción del Articulo
Purpose. This paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods. Design/methodology/approach. Many VaR estimation models have bee...
Autores: | , |
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Formato: | artículo |
Fecha de Publicación: | 2021 |
Institución: | Universidad ESAN |
Repositorio: | ESAN-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.esan.edu.pe:20.500.12640/2829 |
Enlace del recurso: | https://revistas.esan.edu.pe/index.php/jefas/article/view/557 https://hdl.handle.net/20.500.12640/2829 https://doi.org/10.1108/JEFAS-03-2021-0009 |
Nivel de acceso: | acceso abierto |
Materia: | Value at risk GARCH CaViaR MILA ASEAN Valor en riesgo https://purl.org/pe-repo/ocde/ford#5.02.04 |
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dc.title.en_EN.fl_str_mv |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
title |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
spellingShingle |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets Serrano Bautista, Ramona Value at risk GARCH CaViaR MILA ASEAN Valor en riesgo GARCH CaViaR MILA ASEAN https://purl.org/pe-repo/ocde/ford#5.02.04 |
title_short |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
title_full |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
title_fullStr |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
title_full_unstemmed |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
title_sort |
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets |
author |
Serrano Bautista, Ramona |
author_facet |
Serrano Bautista, Ramona Núñez Mora, José Antonio |
author_role |
author |
author2 |
Núñez Mora, José Antonio |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Serrano Bautista, Ramona Núñez Mora, José Antonio |
dc.subject.en_EN.fl_str_mv |
Value at risk GARCH CaViaR MILA ASEAN |
topic |
Value at risk GARCH CaViaR MILA ASEAN Valor en riesgo GARCH CaViaR MILA ASEAN https://purl.org/pe-repo/ocde/ford#5.02.04 |
dc.subject.es_ES.fl_str_mv |
Valor en riesgo GARCH CaViaR MILA ASEAN |
dc.subject.ocde.none.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#5.02.04 |
description |
Purpose. This paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods. Design/methodology/approach. Many VaR estimation models have been presented in the literature. In this paper, the VaR is estimated using the Generalized Autoregressive Conditional Heteroskedasticity, EGARCH and GJR-GARCH models under normal, skewed-normal, Student-t and skewed-Student-t distributional assumptions and compared with the predictive performance of the Conditional Autoregressive Value-at-Risk (CaViaR) considering the four alternative specifications proposed by Engle and Manganelli (2004). Findings. The results support the robustness of the CaViaR model in out-sample VaR forecasting for the MILA and ASEAN-5 emerging stock markets in crisis periods. This evidence is based on the results of the backtesting approach that analyzed the predictive performance of the models according to their accuracy. Originality/value. An important issue in market risk is the inaccurate estimation of risk since different VaR models lead to different risk measures, which means that there is not yet an accepted method for all situations and markets. In particular, quantifying and forecasting the risk for the MILA and ASEAN-5 stock markets is crucial for evaluating global market risk since the MILA is the biggest stock exchange in Latin America and the ASEAN region accounted for 11% of the total global foreign direct investment inflows in 2014. Furthermore, according to the Asian Development Bank, this region is projected to average 7% annual growth by 2025. |
publishDate |
2021 |
dc.date.accessioned.none.fl_str_mv |
2022-01-25T20:02:03Z |
dc.date.available.none.fl_str_mv |
2022-01-25T20:02:03Z |
dc.date.issued.fl_str_mv |
2021-12-19 |
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/557 |
dc.identifier.citation.none.fl_str_mv |
Serrano Bautista, R., & Núñez Mora, J. A. (2021). Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets. Journal of Economics, Finance and Administrative Science, 26(52), 197–221. https://doi.org/10.1108/JEFAS-03-2021-0009 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12640/2829 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1108/JEFAS-03-2021-0009 |
url |
https://revistas.esan.edu.pe/index.php/jefas/article/view/557 https://hdl.handle.net/20.500.12640/2829 https://doi.org/10.1108/JEFAS-03-2021-0009 |
identifier_str_mv |
Serrano Bautista, R., & Núñez Mora, J. A. (2021). Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets. Journal of Economics, Finance and Administrative Science, 26(52), 197–221. https://doi.org/10.1108/JEFAS-03-2021-0009 |
dc.language.none.fl_str_mv |
Inglés |
dc.language.iso.none.fl_str_mv |
eng |
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Inglés |
language |
eng |
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urn:issn:2218-0648 |
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https://revistas.esan.edu.pe/index.php/jefas/article/view/557/469 |
dc.rights.en.fl_str_mv |
Attribution 4.0 International |
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info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0/ |
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Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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application/pdf |
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Universidad ESAN. ESAN Ediciones |
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PE |
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Universidad ESAN. ESAN Ediciones |
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Universidad ESAN |
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Serrano Bautista, RamonaNúñez Mora, José Antonio2022-01-25T20:02:03Z2022-01-25T20:02:03Z2021-12-19https://revistas.esan.edu.pe/index.php/jefas/article/view/557Serrano Bautista, R., & Núñez Mora, J. A. (2021). Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets. Journal of Economics, Finance and Administrative Science, 26(52), 197–221. https://doi.org/10.1108/JEFAS-03-2021-0009https://hdl.handle.net/20.500.12640/2829https://doi.org/10.1108/JEFAS-03-2021-0009Purpose. This paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods. Design/methodology/approach. Many VaR estimation models have been presented in the literature. In this paper, the VaR is estimated using the Generalized Autoregressive Conditional Heteroskedasticity, EGARCH and GJR-GARCH models under normal, skewed-normal, Student-t and skewed-Student-t distributional assumptions and compared with the predictive performance of the Conditional Autoregressive Value-at-Risk (CaViaR) considering the four alternative specifications proposed by Engle and Manganelli (2004). Findings. The results support the robustness of the CaViaR model in out-sample VaR forecasting for the MILA and ASEAN-5 emerging stock markets in crisis periods. This evidence is based on the results of the backtesting approach that analyzed the predictive performance of the models according to their accuracy. Originality/value. An important issue in market risk is the inaccurate estimation of risk since different VaR models lead to different risk measures, which means that there is not yet an accepted method for all situations and markets. In particular, quantifying and forecasting the risk for the MILA and ASEAN-5 stock markets is crucial for evaluating global market risk since the MILA is the biggest stock exchange in Latin America and the ASEAN region accounted for 11% of the total global foreign direct investment inflows in 2014. Furthermore, according to the Asian Development Bank, this region is projected to average 7% annual growth by 2025.Propósito: Este artículo prueba la exactitud de los modelos que predicen el valor en riesgo (VaR) para los mercados bursátiles emergentes de Mercado Integrado de América Latina (MILA) y la Asociación de Naciones del Sudeste Asiático (ASEAN) durante períodos de crisis. Diseño/metodología/enfoque: En la literatura se han presentado muchos modelos de estimación del VaR. En este artículo, el VaR se estima utilizando los modelos de heterocedasticidad condicional autorregresiva generalizada, EGARCH y GJR-GARCH bajo supuestos distribucionales normal, normal sesgado, t de Student y t de Student sesgado y se compara con el rendimiento predictivo del Valor en Riesgo Condicional Autorregresivo por Regresiones Cuantiles (CaViaR) considerando las cuatro especificaciones alternativas propuestas por Engle y Manganelli (2004). Hallazgos: Los resultados respaldan la solidez del modelo CaViaR en el pronóstico de VaR fuera de la muestra para los mercados bursátiles emergentes MILA y ASEAN-5 en períodos de crisis. Esta evidencia se basa en los resultados del enfoque de backtesting que analizó el rendimiento predictivo de los modelos según su precisión. Originalidad/valor: Una cuestión importante en el riesgo de mercado es la estimación inexacta del riesgo, ya que diferentes modelos de VaR conducen a diferentes medidas de riesgo, lo que significa que aún no existe un método aceptado para todas las situaciones y mercados. En particular, cuantificar y pronosticar el riesgo para los mercados bursátiles MILA y ASEAN-5 es crucial para evaluar el riesgo del mercado global, ya que MILA es la bolsa de valores más grande de América Latina y la región de la ASEAN representó el 11% del total de la inversión extranjera directa mundial. entradas en 2014. Además, según el Banco Asiático de Desarrollo, se prevé que esta región tenga un crecimiento anual promedio del 7% para 2025.application/pdfInglésengUniversidad ESAN. ESAN EdicionesPEurn:issn:2218-0648https://revistas.esan.edu.pe/index.php/jefas/article/view/557/469Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/Value at riskGARCHCaViaRMILAASEANValor en riesgoGARCHCaViaRMILAASEANhttps://purl.org/pe-repo/ocde/ford#5.02.04Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock marketsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículoreponame:ESAN-Institucionalinstname:Universidad ESANinstacron:ESANJournal of Economics, Finance and Administrative Science2215219726Acceso abiertoTHUMBNAIL52.jpg52.jpgimage/jpeg158570https://repositorio.esan.edu.pe/bitstreams/89685c1a-2f33-475c-9917-6fffb1e7fa56/downloadc90072458ec4c286b649bd4ccb5834c8MD51falseAnonymousREADJEFAS-52-2021-197-221.pdf.jpgJEFAS-52-2021-197-221.pdf.jpgGenerated Thumbnailimage/jpeg6249https://repositorio.esan.edu.pe/bitstreams/056ff522-7f11-4b5e-8eb5-deb4dd08e3eb/download0931051c077a23fe2577e0fd5c214894MD54falseAnonymousREADORIGINALJEFAS-52-2021-197-221.pdfTexto completoapplication/pdf449687https://repositorio.esan.edu.pe/bitstreams/1715aaf3-b4dc-45c8-a965-3200971baf44/downloadca760ba42310ef20d28de620dcf05ad4MD52trueAnonymousREADTEXTJEFAS-52-2021-197-221.pdf.txtJEFAS-52-2021-197-221.pdf.txtExtracted texttext/plain96516https://repositorio.esan.edu.pe/bitstreams/8d8b1795-778c-4a8b-83b9-8a4b6c8dc817/downloada4fb8bad0938edd0ceac5b46d673bddbMD53falseAnonymousREAD20.500.12640/2829oai:repositorio.esan.edu.pe:20.500.12640/28292025-07-09 09:29:30.59https://creativecommons.org/licenses/by/4.0/Attribution 4.0 Internationalopen.accesshttps://repositorio.esan.edu.peRepositorio Institucional ESANrepositorio@esan.edu.pe |
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