A GARCH tutorial with R

Bibliographic Details
Main Author: Perlin, Marcelo Scherer
Publication Date: 2021
Other Authors: Mastella, Mauro, Vancin, Daniel Francisco, Ramos, Henrique Pinto
Format: Article
Language: eng
Source: Repositório Institucional da UFRGS
Download full: http://hdl.handle.net/10183/220139
Summary: Context: modeling volatility is an advanced technique in financial econometrics, with several applications for academic research. Objective: in this tutorial paper, we will address the topic of volatility modeling in R. We will discuss the underlying logic of GARCH models, their representation and estimation process, along with a descriptive example of a real-world application of volatility modeling. Methods: we use a GARCH model to predict how much time it will take, after the latest crisis, for the Ibovespa index to reach its historical peak once again. The empirical data covers the period between years 2000 and 2020, including the 2009 financial crisis and the current 2020’s episode of the COVID-19 pandemic. Conclusion: we find that, according to our GARCH model, Ibovespa is more likely than not to reach its peak once again in one year and four months from June 2020. All data and R code used to produce this tutorial are freely available on the internet and all results can be easily replicated.
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spelling Perlin, Marcelo SchererMastella, MauroVancin, Daniel FranciscoRamos, Henrique Pinto2021-04-21T04:27:09Z20211415-6555http://hdl.handle.net/10183/220139001123234Context: modeling volatility is an advanced technique in financial econometrics, with several applications for academic research. Objective: in this tutorial paper, we will address the topic of volatility modeling in R. We will discuss the underlying logic of GARCH models, their representation and estimation process, along with a descriptive example of a real-world application of volatility modeling. Methods: we use a GARCH model to predict how much time it will take, after the latest crisis, for the Ibovespa index to reach its historical peak once again. The empirical data covers the period between years 2000 and 2020, including the 2009 financial crisis and the current 2020’s episode of the COVID-19 pandemic. Conclusion: we find that, according to our GARCH model, Ibovespa is more likely than not to reach its peak once again in one year and four months from June 2020. All data and R code used to produce this tutorial are freely available on the internet and all results can be easily replicated.application/pdfengRevista de administração contemporânea. Rio de Janeiro, RJ. Vol. 25, no. 1 (2021), p. 1-16VolatilidadeEconometriaMercado de açõesVolatilityGARCHTutorialA GARCH tutorial with RUm tutorial sobre Modelos Garch no R info:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001123234.pdf.txt001123234.pdf.txtExtracted Texttext/plain62976http://www.lume.ufrgs.br/bitstream/10183/220139/2/001123234.pdf.txt8fcf47ed136706caa726a15a4ed97f45MD52ORIGINAL001123234.pdfTexto completo (inglês)application/pdf2795559http://www.lume.ufrgs.br/bitstream/10183/220139/1/001123234.pdf3d14043f15943e838f8de480b134b2ddMD5110183/2201392021-05-07 04:58:43.939446oai:www.lume.ufrgs.br:10183/220139Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-05-07T07:58:43Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv A GARCH tutorial with R
dc.title.alternative.pt.fl_str_mv Um tutorial sobre Modelos Garch no R
title A GARCH tutorial with R
spellingShingle A GARCH tutorial with R
Perlin, Marcelo Scherer
Volatilidade
Econometria
Mercado de ações
Volatility
GARCH
Tutorial
title_short A GARCH tutorial with R
title_full A GARCH tutorial with R
title_fullStr A GARCH tutorial with R
title_full_unstemmed A GARCH tutorial with R
title_sort A GARCH tutorial with R
author Perlin, Marcelo Scherer
author_facet Perlin, Marcelo Scherer
Mastella, Mauro
Vancin, Daniel Francisco
Ramos, Henrique Pinto
author_role author
author2 Mastella, Mauro
Vancin, Daniel Francisco
Ramos, Henrique Pinto
author2_role author
author
author
dc.contributor.author.fl_str_mv Perlin, Marcelo Scherer
Mastella, Mauro
Vancin, Daniel Francisco
Ramos, Henrique Pinto
dc.subject.por.fl_str_mv Volatilidade
Econometria
Mercado de ações
topic Volatilidade
Econometria
Mercado de ações
Volatility
GARCH
Tutorial
dc.subject.eng.fl_str_mv Volatility
GARCH
Tutorial
description Context: modeling volatility is an advanced technique in financial econometrics, with several applications for academic research. Objective: in this tutorial paper, we will address the topic of volatility modeling in R. We will discuss the underlying logic of GARCH models, their representation and estimation process, along with a descriptive example of a real-world application of volatility modeling. Methods: we use a GARCH model to predict how much time it will take, after the latest crisis, for the Ibovespa index to reach its historical peak once again. The empirical data covers the period between years 2000 and 2020, including the 2009 financial crisis and the current 2020’s episode of the COVID-19 pandemic. Conclusion: we find that, according to our GARCH model, Ibovespa is more likely than not to reach its peak once again in one year and four months from June 2020. All data and R code used to produce this tutorial are freely available on the internet and all results can be easily replicated.
publishDate 2021
dc.date.accessioned.fl_str_mv 2021-04-21T04:27:09Z
dc.date.issued.fl_str_mv 2021
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Revista de administração contemporânea. Rio de Janeiro, RJ. Vol. 25, no. 1 (2021), p. 1-16
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eu_rights_str_mv openAccess
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