In this paper, we investigate the predictability of technical indicators on energy futures volatility from the high-frequency and high-dimensional perspectives. We show that the technical indicators have significant impacts on crude oil and natural gas futures volatility based on in- and out-of-sample analysis. Further, we analyze the impacts of interactions among predictor variables on future volatility. Based on an improved conditional sure independence screening model, we find that the interactions contribute to the out-of-sample predictive power significantly. The improved model has robust and better forecasting performance relative to extant popular dimension reduction methods, forecast combination methods, and regularization methods. Moreover, we show that the out-of-sample predictability is robust during various periods. Finally, we show that technical indicators improve economic value in the crude oil market but the economic increment is not significant in the natural gas market.

在本文中，我们从高频和高维的角度研究技术指标对能源期货波动率的可预测性。我们表明，基于样本内和样本外分析，技术指标对原油和天然气期货波动具有重大影响。此外，我们分析了预测变量之间的相互作用对未来波动的影响。基于改进的条件确定独立性筛选模型，我们发现交互作用对样本外预测能力有显着贡献。相对于现存流行的降维方法、预测组合方法和正则化方法，改进后的模型具有鲁棒性和更好的预测性能。此外，我们表明样本外的可预测性在不同时期都是稳健的。最后，