We use a quantile-regression heterogeneous autoregressive realized volatility (QR-HAR-RV) model to study whether geopolitical risks have predictive value in sample and out-of-sample for realized gold-returns volatility estimated from intradaily data. We consider overall geopolitical risks along with a decomposition into actual risks (i.e., acts) and threats, and we control for overall the impact of economic policy uncertainty (EPU). We find that, after controlling for EPU, the components of geopolitical risks have predictive power for realized volatility mainly at a longer forecast horizon when we account for the potential asymmetry of the loss function a forecaster uses to evaluate forecasts.