Academic literature on the topic 'Box-Jenkins methodology'

Made available in DSpace on 2016-04-26T20:48:37Z (GMT). No. of bitstreams: 1 Emerson Oliveira de Queiros.pdf: 1394134 bytes, checksum: e8f7b40ddc426553915a8ec319148ce7 (MD5) Previous issue date: 2012-08-24<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>The goal of the present work it to use the Box-Jenkins methodology, also known as ARIMA methodology, to build a short-term model of prediction for the state tax (ICMS) revenue. This tax is the most important source of income for the states in Brazil. Therefore, to predict precisely the volume of resources to be collected, other then being a legal requirement, may also be crucial for the financial management of the States. The results achieved indicate that the Box-Jenkins methodology can be a useful tool to forecast the short-term tax revenue from taxes with the characteristics of the ICMS (Value Add Tax)<br>O presente trabalho objetiva aplicar a metodologia Box-Jenkins, conhecida também como metodologia ARIMA, a fim de construir um modelo de previsão de curto prazo para o imposto estadual (ICMS). Trata-se de um imposto de grande peso relativo nas receitas dos estados no Brasil. Portanto, antecipar precisamente o volume de recursos advindos da principal fonte de receita dos estados no Brasil, além de ser uma imposição legal, pode ser também crucial na gestão financeira dos Estados. Os resultados indicaram que a metodologia Box-Jenkins pode ser uma ferramenta útil se a intenção for construir um modelo de previsão de curto prazo para o imposto com as características do ICMS

This research was designed to develop and evaluate an automated alternative to the Box-Jenkins method of forecasting. The study involved two major phases. The first phase was the formulation of an automated ARIMA method; the second was the combination of forecasts from the automated ARIMA with forecasts from two other automated methods, the Holt-Winters method and the Stepwise Autoregressive method. The development of the automated ARIMA, based on a decision criterion suggested by Akaike, borrows heavily from the work of Ang, Chuaa and Fatema. Seasonality and small data set handling were some of the modifications made to the original method to make it suitable for use with a broad range of time series. Forecasts were combined by means of both the simple average and a weighted averaging scheme. Empirical and generated data were employed to perform the forecasting evaluation. The 111 sets of empirical data came from the M-Competition. The twenty-one sets of generated data arose from ARIMA models that Box, Taio and Pack analyzed using the Box-Jenkins method. To compare the forecasting abilities of the Box-Jenkins and the automated ARIMA alone and in combination with the other two methods, two accuracy measures were used. These measures, which are free of magnitude bias, are the mean absolute percentage error (MAPE) and the median absolute percentage error (Md APE).

This thesis is focused on two demographic processes -- nuptiality and divorce rate. The goal of this thesis is to analyze past, present and future development of nuptiality and divorce rate in Czech Republic and to draw a comparison between this development and the development in selected countries of European Union. The evaluation of the past and present development is made by using selected indicators of nuptiality and divorce rate. The forecast of the future development is obtained by using the Box-Jenkins methodology. The comparison of nuptiality and divorce rate in Czech Republic and in selected countries of European Union (Italy, Netherlands, Slovakia, Spain and Sweden) is to be found in the last chapter of this thesis.

The deregulation of the Electricity Sector in US has led to a tremendous increase in the inter-regional wholesale electricity trade between neighboring utilities or regions. For instance, the generation deficit regions may choose to import power from surplus regions; thus the wholesale electricity market prices in the regions are also affected by the dynamics of its electricity trade with other regions. Valuable insights into such imports/exports ahead of time have become crucial market intelligence for the various academicians and the market players associated with the industry. In this thesis, the task of short-term forecasting of the power flows over three major transmission interties of the Pacific Northwest region, namely the Pacific AC Intertie, the Pacific DC Intertie and the Northern Intertie, is successfully accomplished. The Pacific AC and the Pacific DC interties connect the Pacific Northwest region of US with the state of California. The Northern Intertie is the only intertie connecting the British Columbia region in Canada with the Pacific Northwest US. Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) and Transfer function methodologies are used as the statistical tools to identify the forecasting models in this thesis. The data requirement for all of the models is restricted to publicly available data.<br>Master of Science

The unemployment is one of the main economic indicators. Thanks to time series analysis and predicting values, we can take measures of eliminating negative aspects of the unemployment in the economy. This thesis is concentrated on connection between theory of unemployment with time series analysis of unemployment rate, especially based on Box-Jenkins methodology.

A pesquisa tem como objetivo obter previsões para o mercado de fretes do açúcar para exportação no Estado de São Paulo. Para cumprir tal objetivo, utilizou-se a metodologia Box- Jenkins de séries temporais. O período compreendido na pesquisa foi janeiro de 2006 a setembro de 2013. Foram delimitadas no Estado de São Paulo nove regiões para análise: Ribeirão Preto, Jaú, Araraquara, Presidente Prudente, Araçatuba, Piracicaba, São José do Rio Preto, Pirassununga e Assis. Essas regiões também foram agregadas com o objetivo de obter previsões para o Estado de São Paulo. As previsões foram realizadas fora da amostra correspondendo ao período de outubro de 2012 a setembro de 2013. Os modelos estimados, de forma geral, obtiveram um bom desempenho considerando os cinco primeiros meses de previsão, como o ocorrido nas regiões de Jaú, Araraquara, Piracicaba, Pirassununga e Assis. Dentre as nove regiões analisadas, os modelos ajustados para as Regiões de Piracicaba e Assis apresentaram melhores desempenhos, fato este comprovado pelos menores valores do Erro Quadrático Médio e Soma do Quadrado dos Desvios. Considerando os resultados gerais das nove regiões e da análise do Estado de São Paulo de forma agregada, houve predomínio do emprego do modelo ARIMA como melhor método para a realização de previsões para o mercado de fretes do açúcar. Não obstante, as previsões geradas pela metodologia Box- Jenkins, no curto prazo, constituem em boa ferramenta de auxílio para tomada de decisões e planejamento dos agentes envolvidos no mercado do açúcar.<br>The research aims to obtain predictions for the freights market of sugar for export in the State of São Paulo in Brazil. A Box-Jenkins time series methodology was used to fulfill this objective. The survey was performed from January 2006 through September 2013. Nine regions in São Paulo State were placed for analysis: Ribeirão Preto, Jaú, Araçatuba, Araraquara, Piracicaba, São José do Rio Preto, Pirassununga, Presidente Prudente and Assis and also these regions were aggregated in order to obtain estimates for the State of São Paulo. The predictions were made out of the sample corresponding to the period from October 2012 to September 2013. The estimated models generally presented good performance considering the five first months of forecast, as occurred in the regions of Jaú, Araraquara, Piracicaba, Pirassununga and São José do Rio Preto. Out of the nine regions analyzed, the models adjusted for the regions of Piracicaba and Assis showed better performances, proven by the lowest average square error and Sum of Squares of deviations. Considering the overall results of the nine regions and the analysis of the state of São Paulo aggregated, employment ARIMA model predominated as the best method for performing predictions for the freight market sugar. Nevertheless, the forecasts generated by the Box-Jenkins methodology, in a short term, constitute good tool to aid decision-making and planning of the agents involved in the sugar market.

The aim of the thesis mainly is to understand an issue of time series analysis. There are many methods in time series analysis, but purpose of this analysis persists the same, which is a construction of sufficient model of time series and his application in forecasting of time series. We have to make a basic identification of time series to establish right process in model constructing. The first and the second chapter is devoted to this basic identification. There are many methods, how we said before, for constructing of concrete model. In this thesis, exactly in the third chapter, we introduce one of the most flexible methodology of model constructing. That is The Box-Jenkins methodology, which was defined in 1976 by these men. In the last chapter we try to put to use insight in the issue of time series analysis for comparison and separation of the space of time series and this comparison use for the right interpretation of the parameters of time series model. The diploma project was supported by project from MSMT of the Czech Republic no. 1M06047 "Centre for Quality and Reliability of Production".

This work concerns the creation of automatized procedure of ARIMA and SARIMA class model choice according to Box-Jenkins methodology and in this connection, also deals with force testing of unit roots and analysis of applying of informatics criteria when choosing a model. The goal of this work is to create an application in the environment R that can automatically choose a model of time array generating process. The procedure is verified by a simulation study. In this work an effect of values of generating ARMA (1,1) model processes parameters is examined, for his choice and power of KPSS test, augmented Dickey-Fuller and Phillips-Peron test of unit roots.

This master thesis is divided into two parts. First part focuses on production and consumption of electricity in the Czech republic, describing sources of the production and their progress since 1990, considering also the main electricity consumers. The end of the first part focuses on the Box-Jenkins methodology, time series of electricity consumption between 1981 and 2008 are created as well as forecasted up to 2011. The second part of this thesis describes the cluster analysis. This is used for finding similarities of the 27 states of the European Union. Cluster analysis is applied for years 1990 and 2007, for both electric power production and electric power consumption.