Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | BBR. Brazilian Business Review (English edition. Online) |
Texto Completo: | http://www.bbronline.com.br/index.php/bbr/article/view/106 |
Resumo: | This study aimed to forecast the prices of a group of commodities through the multivariate spectral analysis model and compare them with those obtained by classical forecasting and neural network models. The choice of commodities such as ethanol, cattle, corn, coffee and soy was due to the emphasis in the exports in 2013. The multivariate spectral model has proved to be suitable, when compared with others, by enabling a better predictive performance. The results obtained in the out-of-sample period, through the use of measurement error and statistical test, confirm this. This research may help market professionals in formulating and implementing policies targeted to the agricultural sector due to the relevance of price forecast as a planning instrument and analysis of the finance market behavior for those who need protection against price fluctuations. |
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Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&FbovespaPrevisão de Preços Através da Análise Espectral Multivariada: Evidências para Commodities da BM&FbovespaSpectrum analysisForecastCommoditiesAnálise espectralprevisãocommoditiesThis study aimed to forecast the prices of a group of commodities through the multivariate spectral analysis model and compare them with those obtained by classical forecasting and neural network models. The choice of commodities such as ethanol, cattle, corn, coffee and soy was due to the emphasis in the exports in 2013. The multivariate spectral model has proved to be suitable, when compared with others, by enabling a better predictive performance. The results obtained in the out-of-sample period, through the use of measurement error and statistical test, confirm this. This research may help market professionals in formulating and implementing policies targeted to the agricultural sector due to the relevance of price forecast as a planning instrument and analysis of the finance market behavior for those who need protection against price fluctuations.Esta pesquisa teve como proposta realizar previsões dos preços de um grupo de commodities através do modelo espectral de análise multivariada e compará-las com aquelas obtidas por modelos clássicos de previsão e de redes neurais. A escolha das commodities etanol, boi gordo, milho, café e soja deu-se por conta do destaque na pauta de exportações no ano de 2013. O modelo espectral multivariado demonstrou-se adequado, quando comparado com os demais, ao permitir melhores desempenhos preditivos. Os resultados obtidos no período fora da amostra, mediante o uso das medidas de erro e do teste estatístico, confirmam isso. A pesquisa pode auxiliar os profissionais do mercado na formulação e aplicação de políticas direcionadas ao setor agrícola por conta da relevância da previsão dos preços como instrumento de planejamento bem como na análise do comportamento do mercado financeiro para aqueles que necessitam de proteção a oscilações dos preços.FUCAPE Business Shool2016-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed ArticleArtigo revisado pelos paresapplication/pdfapplication/pdfhttp://www.bbronline.com.br/index.php/bbr/article/view/10610.15728/bbr.2016.13.5.6Brazilian Business Review; Vol. 13 No. 5 (2016): September to Octomber 2016; 129-157Brazilian Business Review; v. 13 n. 5 (2016): Setembro a Outubro de 2016; 129-1571808-23861807-734Xreponame:BBR. Brazilian Business Review (English edition. Online)instname:Fucape Business School (FBS)instacron:FBSengporhttp://www.bbronline.com.br/index.php/bbr/article/view/106/154http://www.bbronline.com.br/index.php/bbr/article/view/106/155Pinheiro, Carlos Alberto OrgeSenna, Valter deinfo:eu-repo/semantics/openAccess2018-10-31T19:05:03Zoai:ojs.pkp.sfu.ca:article/106Revistahttps://www.bbronline.com.br/index.php/bbr/indexONGhttp://www.bbronline.com.br/index.php/bbr/oai|| bbronline@bbronline.com.br1808-23861808-2386opendoar:2018-10-31T19:05:03BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)false |
dc.title.none.fl_str_mv |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa Previsão de Preços Através da Análise Espectral Multivariada: Evidências para Commodities da BM&Fbovespa |
title |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
spellingShingle |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa Pinheiro, Carlos Alberto Orge Spectrum analysis Forecast Commodities Análise espectral previsão commodities |
title_short |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
title_full |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
title_fullStr |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
title_full_unstemmed |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
title_sort |
Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa |
author |
Pinheiro, Carlos Alberto Orge |
author_facet |
Pinheiro, Carlos Alberto Orge Senna, Valter de |
author_role |
author |
author2 |
Senna, Valter de |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Pinheiro, Carlos Alberto Orge Senna, Valter de |
dc.subject.por.fl_str_mv |
Spectrum analysis Forecast Commodities Análise espectral previsão commodities |
topic |
Spectrum analysis Forecast Commodities Análise espectral previsão commodities |
description |
This study aimed to forecast the prices of a group of commodities through the multivariate spectral analysis model and compare them with those obtained by classical forecasting and neural network models. The choice of commodities such as ethanol, cattle, corn, coffee and soy was due to the emphasis in the exports in 2013. The multivariate spectral model has proved to be suitable, when compared with others, by enabling a better predictive performance. The results obtained in the out-of-sample period, through the use of measurement error and statistical test, confirm this. This research may help market professionals in formulating and implementing policies targeted to the agricultural sector due to the relevance of price forecast as a planning instrument and analysis of the finance market behavior for those who need protection against price fluctuations. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-09-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Artigo revisado pelos pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.bbronline.com.br/index.php/bbr/article/view/106 10.15728/bbr.2016.13.5.6 |
url |
http://www.bbronline.com.br/index.php/bbr/article/view/106 |
identifier_str_mv |
10.15728/bbr.2016.13.5.6 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
http://www.bbronline.com.br/index.php/bbr/article/view/106/154 http://www.bbronline.com.br/index.php/bbr/article/view/106/155 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
FUCAPE Business Shool |
publisher.none.fl_str_mv |
FUCAPE Business Shool |
dc.source.none.fl_str_mv |
Brazilian Business Review; Vol. 13 No. 5 (2016): September to Octomber 2016; 129-157 Brazilian Business Review; v. 13 n. 5 (2016): Setembro a Outubro de 2016; 129-157 1808-2386 1807-734X reponame:BBR. Brazilian Business Review (English edition. Online) instname:Fucape Business School (FBS) instacron:FBS |
instname_str |
Fucape Business School (FBS) |
instacron_str |
FBS |
institution |
FBS |
reponame_str |
BBR. Brazilian Business Review (English edition. Online) |
collection |
BBR. Brazilian Business Review (English edition. Online) |
repository.name.fl_str_mv |
BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS) |
repository.mail.fl_str_mv |
|| bbronline@bbronline.com.br |
_version_ |
1754732237018890240 |