BVG Index Risk and Return: Econometric Analysis and Projection

The objective of this research is to analyze the behavior of the returns and the volatility of the BVG Index for the period 2012-2017. Through an ARIMA model, it is to predict the monthly returns of the BVG Index for the year 2018. The methodology that this study is not experimental. To determine th...

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Autores principales: Espín Esparza, Emilia, Jácome Gagñay, Renato, Vera Pianda, Pamela
Formato: Artículo revista
Lenguaje:Español
Publicado: Facultad de Ciencias Económicas. Instituto de Economía y Finanzas 2021
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Acceso en línea:https://revistas.unc.edu.ar/index.php/acteconomica/article/view/28763
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id I10-R10article-28763
record_format ojs
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-10
container_title_str Revistas de la UNC
language Español
format Artículo revista
topic Ecuador
Guayaquil stock exchange
volatility
ARIMA
Ecuador
olsa de valores de Guayaquil
volatilidad
ARIMA
spellingShingle Ecuador
Guayaquil stock exchange
volatility
ARIMA
Ecuador
olsa de valores de Guayaquil
volatilidad
ARIMA
Espín Esparza, Emilia
Jácome Gagñay, Renato
Vera Pianda, Pamela
BVG Index Risk and Return: Econometric Analysis and Projection
topic_facet Ecuador
Guayaquil stock exchange
volatility
ARIMA
Ecuador
olsa de valores de Guayaquil
volatilidad
ARIMA
author Espín Esparza, Emilia
Jácome Gagñay, Renato
Vera Pianda, Pamela
author_facet Espín Esparza, Emilia
Jácome Gagñay, Renato
Vera Pianda, Pamela
author_sort Espín Esparza, Emilia
title BVG Index Risk and Return: Econometric Analysis and Projection
title_short BVG Index Risk and Return: Econometric Analysis and Projection
title_full BVG Index Risk and Return: Econometric Analysis and Projection
title_fullStr BVG Index Risk and Return: Econometric Analysis and Projection
title_full_unstemmed BVG Index Risk and Return: Econometric Analysis and Projection
title_sort bvg index risk and return: econometric analysis and projection
description The objective of this research is to analyze the behavior of the returns and the volatility of the BVG Index for the period 2012-2017. Through an ARIMA model, it is to predict the monthly returns of the BVG Index for the year 2018. The methodology that this study is not experimental. To determine the ARIMA model, the time series in the study is done in the Gretl software, the model predicts the behavior of BVG Index for the 2018, and it shows a volatility behavior for the index.
publisher Facultad de Ciencias Económicas. Instituto de Economía y Finanzas
publishDate 2021
url https://revistas.unc.edu.ar/index.php/acteconomica/article/view/28763
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AT jacomegagnayrenato riesgoyrendimientodelbvgindexanalisisyproyeccioneconometrica
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