Uncovering predictability in the evolution of the WTI oil futures curve
提出一种函数型时间序列方法建模和预测原油期货，利用经典离散方法忽略的动态过程，在样本外测试中优于基准模型。
Abstract Accurately forecasting the price of oil, the world's most actively traded commodity, is of great importance to both academics and practitioners. We contribute by proposing a functional time series based method to model and forecast oil futures. Our approach boasts a number of theoretical and practical advantages, including effectively exploiting underlying process dynamics missed by classical discrete approaches. We evaluate the finite‐sample performance against established benchmarks using a model confidence set test. A realistic out‐of‐sample exercise provides strong support for the adoption of our approach, which resides in the superior set of models in all considered instances.