I will talk about the pricing of options in a class of discrete-time Flexible Coefficient Generalised Autoregressive Conditional Heteroskedastic (FC-GARCH) models with non-normal innovations. A conditional Esscher transform was used to select a price kernel for valuation in the incomplete market. We provide the risk neutral model when the innovations have a normal distribution. Also, we develop a model to incorporate negative skewness and provide the risk neutral model for a negative shifted-Gamma distribution. Finally, we provide a numerical study to identify some key features of the pricing results.