We decompose economic uncertainty into "good" and "bad" components according to the sign of innovations. Our results indicate that bad uncertainty provides stronger predictive content regarding future market volatility than good uncertainty. The asymmetric models with good and bad uncertainties forecast market volatility in a better way than the symmetric models with overall uncertainty. The combination for asymmetric uncertainty models significantly outperforms the benchmark of autoregression, as well as the combination for symmetric models. The revealed volatility predictability is further demonstrated to be economically significant in the framework of portfolio allocation.

中文翻译：

---

预测总体市场波动：好的和坏的不确定性的作用

根据创新的迹象，我们将经济不确定性分解为“好”和“坏”部分。我们的结果表明，与良好的不确定性相比，不良的不确定性提供了关于未来市场波动的更强的预测内容。具有良好和不利不确定性的非对称模型比具有整体不确定性的对称模型更好地预测市场波动。非对称不确定性模型的组合明显优于自回归的基准，以及对称模型的组合。在投资组合分配的框架内，所显示的波动率可预测性在经济上也具有重要意义。