We study the in- and out-of-sample predictive value of time-varying risk aversion for realized volatility of gold returns via extended heterogeneous autoregressive realized volatility (HAR-RV) models. Our findings suggest that time-varying risk aversion possesses predictive value for gold volatility both in- and out-of-sample. Time-varying risk aversion is found to absorb the in-sample predictive power of n index of economic policy uncertainty at a short forecasting horizon. We also study the out-of-sample predictive power of time-varying risk aversion in the presence of realized higher-moments, jumps, gold returns, a leverage effect as well as an index of economic policy uncertainty in the forecasting model. In addition, we study the role of the shape of the loss function used to evaluate losses from forecast errors for the role of time-varying risk aversion as a predictor of realized volatility. Overall, our findings show that time-varying risk aversion often captures information useful for out-of-sample prediction of realized volatility not already contained in the other predictors.