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dc.contributor.authorPerlin, Marcelo Schererpt_BR
dc.contributor.authorMastella, Mauropt_BR
dc.contributor.authorVancin, Daniel Franciscopt_BR
dc.contributor.authorRamos, Henrique Pintopt_BR
dc.date.accessioned2021-04-21T04:27:09Zpt_BR
dc.date.issued2021pt_BR
dc.identifier.issn1415-6555pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/220139pt_BR
dc.description.abstractContext: 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.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofRevista de administração contemporânea. Rio de Janeiro, RJ. Vol. 25, no. 1 (2021), p. 1-16pt_BR
dc.rightsOpen Accessen
dc.subjectVolatilityen
dc.subjectVolatilidadept_BR
dc.subjectGARCHen
dc.subjectEconometriapt_BR
dc.subjectMercado de açõespt_BR
dc.subjectTutorialen
dc.titleA GARCH tutorial with Rpt_BR
dc.title.alternativeUm tutorial sobre Modelos Garch no R pt
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001123234pt_BR
dc.type.originNacionalpt_BR


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