Doubly stochastic models with GARCH innovations

A rapid development of time series models and methods addressing volatility in computational finance and econometrics are recently reported in the financial literature. This paper considers doubly stochastic volatility models with GARCH errors. General properties for process mean, variance and kurtosis are derived as these results can be used in model identification.