The importance of skewness and kurtosis in the return generating process is assessed by examining the out-of-sample forecasting power of three different Exponential GARCH models that assume the conditional errors are generated by a normal distribution, a generalized error distribution, and a nonparametric distribution. These models are selected because they incorporate the time-series properties of security returns and each of these distributions allows for various degrees of conditional skewness and kurtosis.
