Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Media evidence and previous research have established that geopolitical risk is an important driver of crude oil price volatility. In this paper, we assess whether the importance of geopolitical uncertainty is also ”translated” into valuable predictive information for oil price volatility forecasts. To do so, we construct a ”beauty contest” where we assess the incremental predictive content of geopolitical risk against several other highly important uncertainty indicators, for forecasting horizon up to 22-days ahead. Initially, we use a HAR model which is augmented by each of the uncertainty indicators. Subsequently, we develop a Dynamic Model Averaging (DMA) methodology, where we assess whether the combination of all uncertainty indices (DMA-all), vis-a-vis a DMA model without the geopolitical uncertainty index, exhibits superior predictive performance. Our findings show that geopolitical uncertainty offers superior predictive information when combined with other uncertainty indicators. More importantly, we show that the inclusion of geopolitical uncertainty in a DMA framework generates superior trading profits and risk management measures’ predictions, in comparison with benchmark models, especially in longer-run horizons. Several implications are drawn from these results.