The Promise of Time-Series Foundation Models for Agricultural Forecasting: Evidence from Commodity Prices
时间序列基础模型用于农业预测的潜力:商品价格证据
Forecasting agricultural markets remains challenging due to nonlinear dynamics, structural breaks, and sparse data. A long-standing belief holds that simple time-series methods outperform more advanced alternatives. This paper provides the first systematic evidence that this belief no longer holds with modern time-series foundation models (TSFMs). Using USDA ERS monthly commodity price data from 1997-2025, we evaluate 17 forecasting approaches across four model classes,…