Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue that this is important because such dynamics arise naturally from the dynamic nature of shocks in energy commodities. We identify such dynamics from the data using localised regressions and build a model that significantly improves volatility forecasts. Such forecasting models, based on a rich persistence structure that varies smoothly over time, outperform state-of-the-art benchmark models and are particularly useful for forecasting over longer horizons.

翻译：时间变化与持续性是波动率的关键特性，在能源波动率预测模型中常被分别研究。本文提出一种新方法，允许具有异质持续性的冲击随时间平滑变化，从而将二者共同建模。我们认为这种方法至关重要，因为此类动态特性天然产生于能源商品的冲击动态本质。我们通过局部回归从数据中识别此类动态，并构建了能显著改进波动率预测的模型。这种基于随时间平滑变化的丰富持续性结构的预测模型，其性能优于当前最先进的基准模型，在较长预测范围内尤其有效。