Intermediate term forecasting techniques for management.

Abstract

Autoregressive Integrated Moving Average (ARIMA) forecasts are made for the prices of a variety of commodities one year into the future in an attempt to determine if improved budget accuracy is possible for small businesses dependent upon commodities for the production of goods or services. An average forecast error of less than seven percent is obtained using commonly available ARIMA computer software employable on inexpensive microcomputers. It is concluded small businesses can affordably obtain more accurate commodity price budgets through the use of ARIMA forecasts.