Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina

The aim of this work is to model the volatility pattern during the historical stock return of the most important index of the Buenos Aires Stock Exchange (MERVAL) from January 1 of 2013 to June 6 of 2016, using the family of hybrid Arima-Garch models. The study is based on econometrics bibliography...

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Autores principales: Larre, Tomás Francisco, Auza, Joaquín
Formato: Artículo revista
Lenguaje:Español
Publicado: Ediciones UNL 2020
Materias:
Volatility
Leverage
Conditional Heteroscedasticity
volatilidad
apalancamiento
heteroscedasticidad condicionada
Acceso en línea:https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/CE/article/view/9268
Aporte de:
Biblioteca Virtual - Publicaciones (UNL) de Universidad Nacional del Litoral
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spelling I26-R133-article-92682021-07-13T11:57:55Z Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina Financial Modeling with Hybrid Arima-Garch Models: Evidence for Argentina Larre, Tomás Francisco Auza, Joaquín Volatility Leverage Conditional Heteroscedasticity volatilidad apalancamiento heteroscedasticidad condicionada The aim of this work is to model the volatility pattern during the historical stock return of the most important index of the Buenos Aires Stock Exchange (MERVAL) from January 1 of 2013 to June 6 of 2016, using the family of hybrid Arima-Garch models. The study is based on econometrics bibliography with a focus on stock index modeling for other emerging economies. The conditions to employ this family of models are verified. The analysis confirms the existence of asymmetry and a leverage effect, which is the reason why the asymmetric E-Garch and GJR-Garch models are used, with both normal and student’s t distributions. For different orders of the aforementioned specifications, the models are repeatedly estimated. For the selection of models to use insample, the Schwarz information criterion is opted for. The estimated models are subject to hypothesis testing in order to guarantee compliance with the following properties: each systematic component of the process is taken into account, there are no bias of indicators or magnitude, and there is parameter stability. Then, the out-of-sample forecast performance is tested. Finally, it is observed that the E-Garch ~ t (1, 1), with ARMA (2,0) and ARMA (2,1) models, is superior in-sample and its forecasting performance is not significantly inferior to the other estimated models. El propósito de este trabajo es modelizar el patrón de volatilidad presente en la serie histórica de retornos del principal índice del Mercado de Valores de Buenos Aires (MERVAL) entre el 1 de enero de 2013 y el 6 de junio de 2016, empleando la familia de modelos híbridos ARIMA–GARCH. Se realiza un estudio de literatura econométrica enfocada a la modelización de índices bursátiles para otras economías emergentes. Se verifican las condiciones para el empleo de esta familia de modelos. El análisis confirma la presencia de asimetría y efecto apalancamiento por los que se utilizan modelos asimétricos E–GARCH y GJR–GARCH, tanto con distribución Normal como con distribución t – Student. Se estiman de forma iterativa modelos para distintos órdenes de las especificaciones mencionadas. Para la selección de modelos dentro de la muestra se recurre al Criterio de Información de Schwarz. Se somete los modelos estimados a una secuencia de pruebas de hipótesis a fin de garantizar el cumplimiento de las siguientes propiedades: la captura de todo componente sistemático del proceso, inexistencia de sesgo de signos y magnitud y estabilidad de los parámetros. Posteriormente, se hacen observaciones fuera de la muestra con el fin de evaluar su poder de pronóstico. Finalmente, se constata que el E–GARCH ~ t (1, 1), conmodelos de media ARMA (2,0) y ARMA (2,1) resulta superior dentro de la muestra y su capacidad predictiva no resulta significativamente inferior a la de otros modelos estimados. Ediciones UNL 2020-05-29 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf application/pdf https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/CE/article/view/9268 10.14409/rce.v2i-.9268 Ciencias Económicas; Vol. 2 (16): Ciencias Económicas; 29-45 Ciencias Económicas; Vol. 2 (16): Ciencias Económicas; 29-45 2362-552X 1666-8359 10.14409/rce.v2i0 spa https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/CE/article/view/9268/12596 https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/CE/article/view/9268/12597 Derechos de autor 2020 Tomás Francisco Torres, Joaquín Auza
institution Universidad Nacional del Litoral
institution_str I-26
repository_str R-133
container_title_str Biblioteca Virtual - Publicaciones (UNL)
language Español
format Artículo revista
topic Volatility
Leverage
Conditional Heteroscedasticity
volatilidad
apalancamiento
heteroscedasticidad condicionada
spellingShingle Volatility
Leverage
Conditional Heteroscedasticity
volatilidad
apalancamiento
heteroscedasticidad condicionada
Larre, Tomás Francisco
Auza, Joaquín
Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
topic_facet Volatility
Leverage
Conditional Heteroscedasticity
volatilidad
apalancamiento
heteroscedasticidad condicionada
author Larre, Tomás Francisco
Auza, Joaquín
author_facet Larre, Tomás Francisco
Auza, Joaquín
author_sort Larre, Tomás Francisco
title Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
title_short Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
title_full Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
title_fullStr Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
title_full_unstemmed Modelización financiera mediante modelos híbridos Arima–Garch: evidencia para Argentina
title_sort modelización financiera mediante modelos híbridos arima–garch: evidencia para argentina
description The aim of this work is to model the volatility pattern during the historical stock return of the most important index of the Buenos Aires Stock Exchange (MERVAL) from January 1 of 2013 to June 6 of 2016, using the family of hybrid Arima-Garch models. The study is based on econometrics bibliography with a focus on stock index modeling for other emerging economies. The conditions to employ this family of models are verified. The analysis confirms the existence of asymmetry and a leverage effect, which is the reason why the asymmetric E-Garch and GJR-Garch models are used, with both normal and student’s t distributions. For different orders of the aforementioned specifications, the models are repeatedly estimated. For the selection of models to use insample, the Schwarz information criterion is opted for. The estimated models are subject to hypothesis testing in order to guarantee compliance with the following properties: each systematic component of the process is taken into account, there are no bias of indicators or magnitude, and there is parameter stability. Then, the out-of-sample forecast performance is tested. Finally, it is observed that the E-Garch ~ t (1, 1), with ARMA (2,0) and ARMA (2,1) models, is superior in-sample and its forecasting performance is not significantly inferior to the other estimated models.
publisher Ediciones UNL
publishDate 2020
url https://bibliotecavirtual.unl.edu.ar/publicaciones/index.php/CE/article/view/9268
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first_indexed 2023-07-05T23:04:53Z
last_indexed 2023-07-05T23:04:53Z
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