FORECASTING DEMAND FOR SPECIAL TELEPHONE SERVICES - A CASE-STUDY

Future demand for services or goods is usually forecasted by fitting ARIMA models and using the optimal rules based on the squared error criterion. When analyzing a large number of time series describing Special Services in the telephone business, we found that a model with independent increments with stable distributions was more suitable and led to better predictions. It also described forecast errors adequately. This paper discusses the model, compares it with a state space model which is currently used for the problem, and applies several data analytic procedures to assess how well the model fits the data. A few remarks on the use of estimated forcast error size conclude the paper. © 1990.