In this paper we compare the predictive abilility of Stochastic Volatility (SV) models to that of volatility forecasts implied by option prices. We develop an SV model with implied volatility as an exogeneous variable in the variance equation which facilitates the use of statistical tests for nested models# we refer to this model as the SVX model. The SVX model is then extended to a volatility model with persistence adjustment term and this we call the SVX+ model. This class of SV models can be estimated by quasi maximum likelihood methods but the main emphasis will be on methods for exact maximum likelihood using Monte Carlo importance sampling methods. The performance of the models is evaluated, both within sample and out-of-sample, for daily returns on the Standard & Poor's 100 index. Similar studies have been undertaken with GARCH models where findings were initially mixed but recent research has indicated that implied volatility provides superior forecasts. We find that implied volati..
