Informing Long Term Lumber Buying: A Decision-Making Criteria for Wood Buyers Using a Simple Algorithm

Abstract

Lumber purchasing decisions rely mostly on historic lumber prices, or the corresponding price of their futures. Various, lumber specific, supply and demand conditions lead to an unpredictable weekly price if one employs basic economic and statistics tools. We propose a prediction model that builds on the historical change of the price from week to week to provide purchasing recommendations yearly. We tested our model using data from the Random Lengths weekly price catalog for six lumber types (1995-2014), comparing it to other purchasing strategies created from the spot and futures prices showing that it is better almost always.