* Once your purchase is processed by paypal you will be redirected back to this page and you'll have the option to download the paper. We'll also send the paper to your paypal email address as proof of purchase.Download Paper
Compare and contrast the stationary forecasting model approach with that of a time series forecasting approach. Identify and explain key factors that are relevant in the selection of a specific approach.
Length: 1 pages (275 Words)
Time series forecasting techniques provide forecasts based exclusively on historical values. These methods are widely applied in business situations in which the forecasts of a year or less are needed. A stationary model entails statistical properties like variance, mean, and autocorrelation among others. These factors are constant over time. Time series are better applied in short-term forecasts. Forecasting using time series also uses past data, which is of high quality and clearly representative (Brockwell & Davis, 2013). Time series approaches are best used in stable situations. In cases where there are substantial fluctuations and basic conditions may change, time series may present poor results.