Intermediate Term Forecasting Techniques for Management.
Abstract
In this thesis 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. Additional keywords: hypotheses, mathematical models, mathematical prediction, Box Jenkins method, aluminum, coal, cotton, gasoline, soybeans, steel, tin, zinc. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1984
- Accession Number
- ADA151370
Entities
People
- D. L. Herring
Organizations
- Naval Postgraduate School