Forecast and interactions of the brazilian cellulose prices in the internal and external markets

Detalhes bibliográficos
Autor(a) principal: Reichert, Bianca
Data de Publicação: 2020
Outros Autores: Souza, Adriano Mendonça
Tipo de documento: Artigo
Idioma: por
Título da fonte: Ciência Florestal (Online)
Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/38223
Resumo: The production and export of cellulose are important components of the Brazilian economy. The aim of this research was to predict the domestic and foreign prices of the Brazilian cellulose and to evaluate the interference between its average price sold at wholesale and exported by Brazil. The study focused on data from the Forestry Newsletter of the Center for Advanced Studies on Applied Economics (CEPEA), collected from June 2008 to March 2018. The Autoregressive Integrated Moving Average (ARIMA) models were used to predict the wholesale and export price of cellulose, while the Vector Autoregressive (VAR) model was applied to analyze the inter-relation of these variables. It was observed that the price of wholesale and exported celluloses vary in similar periods, due to the direct relationship with the dollar quotation and with the financial crises in the importing countries. The most accurate model adjusted to predict the wholesale cellulose price was the ARIMA model (1,1,0), while ARFIMAX model (1, d*, 0) obtained the best performance to predict exported cellulose price. Based on the VAR model, there was a correlation between variables, which means that wholesale cellulose price has a strong impact on exported cellulose price. Thus, the methodologies used were effective to predict and analyze the inter-relationships between the variables.
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spelling Forecast and interactions of the brazilian cellulose prices in the internal and external marketsPrevisão e interação dos preços da celulose brasileira nos mercados interno e externoTime seriesARIMA modelsAutoregressive vectorPrice forecastSéries temporaisModelos ARIMAVetor autorregressivoPrevisão do preçoThe production and export of cellulose are important components of the Brazilian economy. The aim of this research was to predict the domestic and foreign prices of the Brazilian cellulose and to evaluate the interference between its average price sold at wholesale and exported by Brazil. The study focused on data from the Forestry Newsletter of the Center for Advanced Studies on Applied Economics (CEPEA), collected from June 2008 to March 2018. The Autoregressive Integrated Moving Average (ARIMA) models were used to predict the wholesale and export price of cellulose, while the Vector Autoregressive (VAR) model was applied to analyze the inter-relation of these variables. It was observed that the price of wholesale and exported celluloses vary in similar periods, due to the direct relationship with the dollar quotation and with the financial crises in the importing countries. The most accurate model adjusted to predict the wholesale cellulose price was the ARIMA model (1,1,0), while ARFIMAX model (1, d*, 0) obtained the best performance to predict exported cellulose price. Based on the VAR model, there was a correlation between variables, which means that wholesale cellulose price has a strong impact on exported cellulose price. Thus, the methodologies used were effective to predict and analyze the inter-relationships between the variables.A produção e a exportação de celulose são componentes importantes da economia no país. O objetivo desta pesquisa foi prognosticar o preço nos mercados interno e externo da celulose brasileira e avaliar a interferência entre o preço médio da celulose vendida em atacado e o preço médio da celulose exportada pelo Brasil. O estudo utilizou dados oriundos do Informativo Florestal do Centro de Estudos Avançados em Economia Aplicada (CEPEA), coletados entre junho de 2008 a março de 2018. Os modelos Autorregressivos Integrados de Médias Móveis (ARIMA) foram utilizados para prognosticar o preço da celulose em atacado e exportada pelo Brasil e, para analisar a inter-relação dessas variáveis, foi aplicado modelo Vetor Autorregressivo (VAR). Observou-se que o preço da celulose em atacado e da celulose exportada sofrem oscilações em períodos semelhantes, devido à relação direta com a cotação do dólar e com as crises financeiras nos países importadores. O modelo de melhor acurácia para prognosticar o preço da celulose em atacado foi o modelo ARIMA (1,1,0) enquanto o modelo ARFIMAX (1, d*,0) obteve o melhor desempenho para prognosticar o preço da celulose exportada. A partir da modelagem VAR, verificou-se a existência de inter-relações entre as variáveis, as quais transpareceram o forte impacto do preço da celulose em atacado sobre o preço da celulose exportada pelo Brasil. Assim, as metodologias empregadas foram eficazes para prognosticar e analisar as inter-relações entre as variáveis.Universidade Federal de Santa Maria2020-06-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/3822310.5902/1980509838223Ciência Florestal; Vol. 30 No. 2 (2020); 501-515Ciência Florestal; v. 30 n. 2 (2020); 501-5151980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/38223/38223Copyright (c) 2020 Ciência Florestalinfo:eu-repo/semantics/openAccessReichert, BiancaSouza, Adriano Mendonça2021-05-20T04:00:47Zoai:ojs.pkp.sfu.ca:article/38223Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2021-05-20T04:00:47Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Forecast and interactions of the brazilian cellulose prices in the internal and external markets
Previsão e interação dos preços da celulose brasileira nos mercados interno e externo
title Forecast and interactions of the brazilian cellulose prices in the internal and external markets
spellingShingle Forecast and interactions of the brazilian cellulose prices in the internal and external markets
Reichert, Bianca
Time series
ARIMA models
Autoregressive vector
Price forecast
Séries temporais
Modelos ARIMA
Vetor autorregressivo
Previsão do preço
title_short Forecast and interactions of the brazilian cellulose prices in the internal and external markets
title_full Forecast and interactions of the brazilian cellulose prices in the internal and external markets
title_fullStr Forecast and interactions of the brazilian cellulose prices in the internal and external markets
title_full_unstemmed Forecast and interactions of the brazilian cellulose prices in the internal and external markets
title_sort Forecast and interactions of the brazilian cellulose prices in the internal and external markets
author Reichert, Bianca
author_facet Reichert, Bianca
Souza, Adriano Mendonça
author_role author
author2 Souza, Adriano Mendonça
author2_role author
dc.contributor.author.fl_str_mv Reichert, Bianca
Souza, Adriano Mendonça
dc.subject.por.fl_str_mv Time series
ARIMA models
Autoregressive vector
Price forecast
Séries temporais
Modelos ARIMA
Vetor autorregressivo
Previsão do preço
topic Time series
ARIMA models
Autoregressive vector
Price forecast
Séries temporais
Modelos ARIMA
Vetor autorregressivo
Previsão do preço
description The production and export of cellulose are important components of the Brazilian economy. The aim of this research was to predict the domestic and foreign prices of the Brazilian cellulose and to evaluate the interference between its average price sold at wholesale and exported by Brazil. The study focused on data from the Forestry Newsletter of the Center for Advanced Studies on Applied Economics (CEPEA), collected from June 2008 to March 2018. The Autoregressive Integrated Moving Average (ARIMA) models were used to predict the wholesale and export price of cellulose, while the Vector Autoregressive (VAR) model was applied to analyze the inter-relation of these variables. It was observed that the price of wholesale and exported celluloses vary in similar periods, due to the direct relationship with the dollar quotation and with the financial crises in the importing countries. The most accurate model adjusted to predict the wholesale cellulose price was the ARIMA model (1,1,0), while ARFIMAX model (1, d*, 0) obtained the best performance to predict exported cellulose price. Based on the VAR model, there was a correlation between variables, which means that wholesale cellulose price has a strong impact on exported cellulose price. Thus, the methodologies used were effective to predict and analyze the inter-relationships between the variables.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/38223
10.5902/1980509838223
url https://periodicos.ufsm.br/cienciaflorestal/article/view/38223
identifier_str_mv 10.5902/1980509838223
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/38223/38223
dc.rights.driver.fl_str_mv Copyright (c) 2020 Ciência Florestal
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Ciência Florestal
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Florestal; Vol. 30 No. 2 (2020); 501-515
Ciência Florestal; v. 30 n. 2 (2020); 501-515
1980-5098
0103-9954
reponame:Ciência Florestal (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Florestal (Online)
collection Ciência Florestal (Online)
repository.name.fl_str_mv Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv ||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br
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