The fundamentals characterizing agricultural commodity prices have often been debated in research and policy circles. Building on limitations in the existing literature, the present study conducts an integrated test and empirically analyses the international price of palm and soybean oil from 1960(1) to 2016(8). For this purpose the univariate Structural Time Series Model based on the state space framework is applied. This approach allows flexibility to model complex stochastic movements, seasonality, cyclical patterns and incorporate intervention analysis. Estimation is based on the Maximum Likelihood method via the Kalman Filter. The results establish that both series exhibit a stochastic long term trend punctuated by multiple breaks. The findings also uncover the presence of cyclicality which results in price swings of varying duration and amplitude. The model works well as a description of oilseed prices and improves awareness of their separate structural components. These are fundamental to design country and commodity specific policy strategies and respond to volatile market conditions. The results underscore that contrary to previous price spikes most of the drivers of the mid 2000s price spikes are structural and on the demand side. These new drivers in oilseed markets suggest the possibility of fundamental change in price behaviour with longer-lasting effects.