Abstract
ABSTRACT We assess the forecast performance of the optimal predictor for returns under asymmetric loss using conditional volatility forecasts from conventional GARCH and realized GARCH models. We compare two classes of models for conditional volatility that is essential to the correction term for the optimal predictor, under asymmetric loss function. We find that when the conditional volatility forecasts from the realized GARCH models are used, the optimal predictor has better performance. The results strongly suggest using conditional volatility forecasts from the joint models of conditional volatility and realized volatility for short-to-moderate forecast horizons and low-to-moderate degrees of asymmetry in the optimal predictor expression to forecast daily returns.
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