The GARCH model and the Stochastic Volatility [SV] model are competing but
non-nested models to describe unobserved volatility in asset returns. We
propose a GARCH model with an additional error term, which can capture SV model
properties, and which can be used to test GARCH against SV. We discuss model
representation, parameter estimation and a simple test for model selection.
Furthermore, we derive the theoretical moments and the autocorrelation function
of our new model. We illustrate its merits for 9 daily stock return series
