We have focused until now on the construction of time series models for stationary and nonstationary series and the determination, assuming the appropriateness of these models, of minimum mean-squared error predictors. If the observed series had in fact been generated by the fitted model, this procedure would give minimum mean-squared error forecasts. In this chapter we discuss three forecasting techniques that have less emphasis on the explicit construction of a model for the data. Each of the three selects, from a limited class of algorithms, the one that is optimal according to specified criteria.
KeywordsARIMA Model Exponential Smoothing Forecast Technique Main Menu Economic Time Series
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