Which Parametric Model for Conditional Skewness?

This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values. We fi nd that an asymmetric GARCH-type specifi cation on shape parameters with a skewed generalized error distribution provides the best in-sample fi t for the data, as well as reasonable predictions of the realized skewness measure. Our empirical fi ndings imply signi ficant asymmetry with respect to positive and negative news in both conditional asymmetry and kurtosis processes