Forecasting the volatility of the Australian dollar using high‐frequency data: Does estimator accuracy improve forecast evaluation?

We compare forecasts of the volatility of the Australian dollar exchange rate to alternative measures of ex post volatility. We develop and apply a simple test for the improvement in the ability of loss functions to distinguish between forecasts when the quality of a volatility estimator is increased. We find that both realized variance and the daily high–low range provide a significant improvement in loss function convergence relative to squared returns. We find that a model of stochastic volatility provides the best forecasts for models that use daily data, and the GARCH(1,1) model provides the best forecast using high‐frequency data.