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Time Series Forecasting Models of Lumber Cash, Futures, and Basis Prices

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This paper reports on the development of autoregressive-integrated-moving-average (ARIMA) forecasting models for (i) various lumber cash prices, (ii) the lumber futures prices, and (iii) the basis series for the lumber cash prices. The ARIMA models are fitted to weekly data by employing Box-Jenkins (1970) time series modeling procedure. Relatively accurate shortrun forecasts are obtained with the cash and futures price series models; however, the utility of the basis series models appears dubious. Forest Sci. 23:268-280.

Keywords: ARIMA models; Box-Jenkins analysis; time series analysis

Document Type: Journal Article

Affiliations: Graduate Student, School of Business, University of Wisconsin-Madison

Publication date: 1977-06-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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