A GARCH Tutorial with R

Marcelo Perlin, Mauro Mastella, Daniel Francisco Vancin and Henrique Pinto Ramos

RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), 2021, vol. 25, issue 1, e200088

Abstract: 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.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://rac.anpad.org.br/index.php/rac/article/view/1420 (text/html)
https://rac.anpad.org.br/index.php/rac/article/download/1420/1517/ (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:abg:anprac:v:25:y:2021:i:1:1420

Access Statistics for this article

RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration) is currently edited by Marcelo de Souza Bispo

More articles in RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration) from ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração
Bibliographic data for series maintained by Information Technology of ANPAD ().