The purpose of this article is to investigate whether various uncertainty measures provide incremental information for the prediction the volatility of crude oil futures under high-frequency heterogeneous autoregressive (HAR) model specifications. Moreover, by considering the information overlap among various uncertainty measures and fully using of the information in various uncertainty measures, this paper uses two prevailing shrinkage methods, the least absolute shrinkage and selection operator (lasso) and elastic nets, to select uncertainty variables during the entire sampling period, before the COVID-19 pandemic and during the COVID-19 pandemic and then uses the HAR model to predict crude oil volatility. The results show that (i) uncertainty measures can be utilized to predict crude oil volatility under the high-frequency framework in both in-sample and out-of-sample analyses. (ii) Because of the information overlap between various uncertainty measures, adding a large number of uncertain variables to the HAR model may not significantly improve the volatility prediction. (iii) Before and during the COVID-19 pandemic, Chicago Board Options Exchange (CBOE) crude oil volatility (OVX) has the greatest impact on crude oil volatility, infectious disease equity market volatility (EMV) exerts a significant influence on crude oil futures volatility forecasts during the COVID-19 period, and CBOE implied volatility (VIX) and the financial stress index (FSI) have substantial impacts on crude oil futures volatility forecasts before COVID-19.

本文的目的是研究在高频异构自回归 (HAR) 模型规范下，各种不确定性度量是否为预测原油期货的波动性提供了增量信息。此外，考虑到各种不确定性测度之间的信息重叠，充分利用各种不确定性测度中的信息，本文采用最小绝对收缩和选择算子（lasso）和弹性网两种流行的收缩方法来选择不确定性变量。在 COVID-19 大流行之前和 COVID-19 大流行期间的整个采样期间，然后使用 HAR 模型预测原油波动性。结果表明，（i）在样本内和样本外分析的高频框架下，不确定性度量可用于预测原油波动率。(ii) 由于各种不确定性度量之间的信息重叠，在 HAR 模型中添加大量不确定变量可能不会显着改善波动率预测。(iii) 在 COVID-19 大流行之前和期间，芝加哥期权交易所 (CBOE) 原油波动率 (OVX) 对原油波动率的影响最大，传染病股票市场波动率 (EMV) 对原油期货产生重大影响COVID-19 期间的波动率预测，以及 CBOE 隐含波动率 (VIX) 和金融压力指数 (FSI) 对 COVID-19 之前的原油期货波动率预测产生重大影响。