In this paper, we employ the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of 19 dollar-based exchange rate returns based on monthly metrics of oil price uncertainty (OPU), and relatively broader global and country-specific energy market-related uncertainty indexes (EUI). We find that the global EUIs tend to perform better than the OPU, highlighting the need to look beyond the oil market to capture energy related uncertainties. The country-specific EUIs outperform the benchmark in a statistically significant manner for at least 14 currencies across the short-, medium-, and long-term forecasting horizons.

中文翻译：

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能源市场不确定性和汇率波动：GARCH-MIDAS 方法


在本文中，我们采用广义自回归条件异方差混合数据采样（GARCH-MIDAS）框架，基于每月的石油价格不确定性（OPU）指标以及相对更广泛的全球范围来预测 19 美元汇率回报的每日波动性。以及特定国家能源市场相关的不确定性指数（EUI）。我们发现，全球 EUI 的表现往往优于 OPU，这凸显出需要将目光投向石油市场以外的领域，以捕捉与能源相关的不确定性。在短期、中期和长期预测范围内，至少 14 种货币的特定国家 EUI 的表现在统计上显着优于基准。