This paper considers how information from the implied volatility (IV) term structure can be harnessed to improve stock return volatility forecasting within the state-of-the-art HAR model. Factors are extracted from the IV term structure and included as exogenous variables in the HAR framework. We found that including slope and curvature factors leads to significant forecast improvements over the HAR benchmark at a range of forecast horizons, compared with the standard HAR model and HAR model with VIX as IV information set.

中文翻译：

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超越波动率指数 (VIX)：利用隐含波动率的期限结构

本文考虑了如何利用来自隐含波动率 (IV) 期限结构的信息来改进最先进的 HAR 模型内的股票回报波动率预测。因子是从 IV 期限结构中提取的，并作为外生变量包含在 HAR 框架中。我们发现，与标准 HAR 模型和以 VIX 作为 IV 信息集的 HAR 模型相比，包括斜率和曲率因素导致在一系列预测范围内对 HAR 基准的预测显着改进。