FORECASTING OF JUDICIAL CONTINGENCY IN ELECTRIC SECTOR COMPANIES: AN APPROACH VIA DYNAMIC REGRESSION AND EXPONENTIAL SMOOTHING / PREVISÃO DE CONTINGÊNCIA JUDICIAL EM EMPRESAS DO SETOR ELÉTRICO: UMA ABORDAGEM VIA REGRESSÃO DINÂMICA E AMORTECIMENTO EXPONENCIAL

AUTOR(ES)
FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

26/08/2011

RESUMO

The aim of this dissertation is to develop short term models to forecast the number of judicial process in electric sector companies. From the methodology point of view, data is analyzed and models using bottom-up strategy is developed. In other words, a simple model is improved step by step until a proper model that fits well the reality is found. From a univariate model it ends up in a dynamic regression model. The models obtained in this study are compared according to some criterion, mainly forecast accuracy. In the end the conclusion is about the efficiency of dynamic regression models for this kind of forecast, which one presents data with serial correlation of residues, commonly present in economic series. In the end, from the estimated values, it´s proposed a mechanism to analyze the economic viability, to encourage or not, actions which are responsible for instigating judicial processes against the company.

ASSUNTO(S)

amortecimento exponencial exponential smoothing modelos de regressao dinamica dynamic regression models previsao de contingencia judicial judicial contingency forecasting

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