This study employs macroeconomic variables and economic indices to forecast natural gas volatility. The out-of-sample results show that the forecasting performance of the macroeconomic variables outperforms the economic indices. Additionally, the forecasting performance of the mixed data sampling model, which combines the least absolute contraction and the selection operator (MIDAS-LASSO), is better than that of other competing models, and it still has a good predictive ability under certain conditions (e.g., business cycles). Our study confirms the superiority of the MIDAS-LASSO model for natural gas volatility forecasting.

中文翻译：

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数据丰富世界中的天然气波动性可预测性

本研究采用宏观经济变量和经济指数来预测天然气的波动性。样本外结果表明，宏观经济变量的预测表现优于经济指数。此外，结合最小绝对收缩和选择算子（MIDAS-LASSO）的混合数据采样模型的预测性能优于其他竞争模型，并且在某些条件下（例如，商业周期）。我们的研究证实了 MIDAS-LASSO 模型在天然气波动率预测中的优越性。