Accurate estimates of volatility parameters are needed in option pricing. Generalized Autoregressive Conditional Heteroscedastic (GARCH) models and Random Coefficient Autoregressive (RCA) models have been used for volatility modelling. Following Thompson and Thavaneswaran(1999) combined estimating functions are used to estimate the parameters in the volatility models. It turns out that the combined estimating function is more informative for autoregressive processes with GARCH errors and for RCA models. The combination of the least squares (LS) estimating function and the least absolute deviation (LAD) estimating function with application to GARCH model error identification is discussed as an application.Recursive estimation for stochastic volatility models and GARCH models are also discussed in some detail.