{"dcterms:modified":"2025-04-02","dcterms:creator":"Harvard Dataverse","@type":"ore:ResourceMap","schema:additionalType":"Dataverse OREMap Format v1.0.1","dvcore:generatedBy":{"@type":"schema:SoftwareApplication","schema:name":"Dataverse","schema:version":"6.6 build 1829-192cdc4","schema:url":"https://github.com/iqss/dataverse"},"@id":"https://dataverse.harvard.edu/api/datasets/export?exporter=OAI_ORE&persistentId=https://doi.org/10.7910/DVN/C4WHUJ","ore:describes":{"author":[{"citation:authorName":"Marcelo Perlin","citation:authorAffiliation":"Universidade Federal do Rio Grande do Sul","authorIdentifierScheme":"ORCID","authorIdentifier":"https://orcid.org/0000-0002-9839-4268"},{"citation:authorName":"Mauro Mastella","citation:authorAffiliation":"Universidade Federal de Ciências da Saúde de Porto Alegre","authorIdentifierScheme":"ORCID","authorIdentifier":"https://orcid.org/0000-0002-7163-9448"},{"citation:authorName":"Daniel Vancin","citation:authorAffiliation":"Universidade do Vale do Rio dos Sinos","authorIdentifierScheme":"ORCID","authorIdentifier":"https://orcid.org/0000-0001-6303-0555"},{"citation:authorName":"Henrique Ramos","citation:authorAffiliation":"Universidade Federal do Rio Grande do Sul"}],"citation:keyword":[{"citation:keywordValue":"GARCH"},{"citation:keywordValue":"Tutorial-article"}],"citation:datasetContact":{"citation:datasetContactName":"Marcelo Perlin","citation:datasetContactAffiliation":"Universidade Federal do Rio Grande do Sul","citation:datasetContactEmail":"marcelo.perlin@ufrgs.br"},"publication":{"publicationCitation":"Perlin, M. S., Mastella, M., Vancin, D. F., & Ramos, H. P. (2021). A GARCH tutorial with R. Journal of Contemporary Administration, 25(1), e200088. https://doi.org/10.1590/1982-7849rac2021200088"},"citation:dsDescription":{"citation:dsDescriptionValue":"Context: Modelling 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 modelling. 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 pandemia. 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All data and R code used to produce this tutorial are freely available on the internet and all results can be easily replicated.","citation:dsDescriptionDate":"2020-07-08"},"citation:depositor":"RAC - Journal of Contemporary Administration","subject":"Business and Management","title":"Replication Data for: A GARCH Tutorial with R","dateOfDeposit":"2020-07-08","@id":"https://doi.org/10.7910/DVN/C4WHUJ","@type":["ore:Aggregation","schema:Dataset"],"schema:version":"1.0","schema:name":"Replication Data for: A GARCH Tutorial with R","schema:dateModified":"Thu Jul 09 19:24:55 UTC 2020","schema:datePublished":"2020-07-09","schema:creativeWorkStatus":"RELEASED","schema:license":"http://creativecommons.org/publicdomain/zero/1.0","dvcore:fileTermsOfAccess":{"dvcore:fileRequestAccess":false},"schema:includedInDataCatalog":"Harvard Dataverse","schema:isPartOf":{"schema:name":"Journal of Contemporary Administration (RAC) Dataverse","@id":"https://dataverse.harvard.edu/dataverse/rac","schema:isPartOf":{"schema:name":"Harvard Dataverse","@id":"https://dataverse.harvard.edu/dataverse/harvard","schema:description":"<span><span><span><h3>Share, archive, and get credit for your data. 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