Um Estudo da previsão de demanda da castanha de caju no comércio exterior cearense através de séries temporais multivariadas

• Ano de defesa: 2013
• Autor(a) principal: Lima, Diego Duarte
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Logística; Comércio internacional; Análise de séries temporais
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/11156

The application of time series in varius areas such as engineering, logistics, operations research and economics, aims to provide the knowledge of the dependency between observations, trends, seasonality and forecasts. Considering the lack of effective supporting methods od logistics planning in the area of foreign trade, the multivariate models habe been presented and used in this work, in the area of time series: vector autoregression (VAR), vector autoregression moving-average (VARMA) and state-space integral equation (SS). These models were used for the analysis of demand forecast, the the bivariate series of value and volume of cashew nut exports from Ceará from 1996 to 2012. The results showed that the model state space was more successful in predicting the variables value and volume over the period that goes from january to march 2013, when compared to other models by the method of root mean squared error, getting the lowest values for those criteria.