We find that combining two important predictors, stock market implied volatility and oil volatility, can improve the predictability of stock return volatility. We also document that the stock market implied volatility provides far more significant predictability than the oil volatility and other nonoil macroeconomic and financial variables. The empirical results show the “kitchen sink” combination approach that using two predictors jointly performs better than not only the univariate regression models which use oil volatility or stock market implied volatility separately but also convex combination of the individual forecasts. This improvement of predictability is also remarkable when we consider the business cycle. Furthermore, the robust test based on different lag lengths and different macroinformation shows that our forecasting strategy is efficient.

中文翻译：

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预测股市波动：一种组合方法

我们发现，将两个重要的预测指标（股市隐含波动率和石油波动率）结合起来可以提高股票收益率波动率的可预测性。我们还证明，股市隐含波动率比石油波动率和其他非石油宏观经济和金融变量提供的意义要大得多。实证结果表明，“厨房汇”组合方法不仅使用油价波动性或股市隐含波动率的单变量回归模型，而且使用单个预测指标的凸组合，联合使用两个预测因子的效果要好得多。当我们考虑业务周期时，这种可预测性的改进也很显着。此外，