Price Forecasting Through Multivariate Spectral Analysis: Evidence for Commodities of BM&Fbovespa

Detalhes bibliográficos
Autor(a) principal: Pinheiro, Carlos Alberto Orge
Data de Publicação: 2016
Outros Autores: Senna, Valter de
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.
id FBS-1_5f15c6585e42bbbe09bcdc38445a6da3
oai_identifier_str oai:ojs.pkp.sfu.ca:article/106
network_acronym_str FBS-1
network_name_str BBR. Brazilian Business Review (English edition. Online)
repository_id_str
spelling 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