A GARCH Tutorial with R

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.

Index Futures Introduction and Stock Market Volatility: Empirical Study in Vietnam

“…Data is processed using R software. For GARCH modelling, this paper uses R code provided by Perlin, Mastella, Vancin and Ramos (2020).…”

Composição e alocação de moedas das reservas internacionais: evidências do Brasil

“…Incorpora-se essa dinâmica assumindo que a variância da taxa de câmbio segue um GARCH (1,1) 3 , já que este tipo de modelo fornece uma função paramétrica simples que pode ser usada para descrever a evolução da volatilidade (Perlin et al, 2020). Diante disso, calcula-se a volatilidade anual das taxas de câmbio de 2002 a 2020 através do modelo GARCH.…”