Dairy commodity prices have become more volatile over the last 10–11 yr. The aim of this paper was to produce reliable price forecasts for the most frequently traded dairy commodities. Altogether five linear and nonlinear time series models were applied. The analysis reveals that prices of dairy commodities reached a structural breakpoint in 2006/2007. The results also show that a combination of linear and nonlinear models is useful in forecasting commodity prices. In this study, the price of cheese is the most difficult to forecast, but a simple autoregressive (AR) model performs reasonably well after 12 mo. Similarly, for butter the AR model performs the best, while for skimmed milk powder (Smp), whole milk powder (Wmp) and whey powder (Whp) the nonlinear methods are the most accurate. However, few of the differences between models are significant according to the Diebold–Mariano (DM) test. The findings could be of interest to the whole dairy industry.

中文翻译：

---

预测乳制品价格——线性和非线性模型的比较

在过去的 10-11 年间，乳制品价格变得更加波动。本文的目的是为交易最频繁的乳制品提供可靠的价格预测。总共应用了五个线性和非线性时间序列模型。分析显示，乳制品价格在 2006/2007 年达到了结构性断点。结果还表明，线性和非线性模型的组合可用于预测商品价格。在这项研究中，奶酪的价格是最难预测的，但一个简单的自回归 (AR) 模型在 12 个月后表现相当不错。同样，对于黄油，AR 模型表现最好，而对于脱脂奶粉 (Smp)、全脂奶粉 (Wmp) 和乳清粉 (Whp)，非线性方法最准确。然而，根据 Diebold-Mariano (DM) 检验，模型之间的差异很少是显着的。这些发现可能会引起整个乳制品行业的兴趣。