This paper focuses on a topical and important area of theory and practice ie. The risk premium in financial markets. While there exists a vast amount of research into its behaviour, particularly in US markets, this is largely based on regression based techniques which do not capture well the dynamic and forward looking nature of the risk premium. In this paper the variation of the unobserved risk premium is modelled by a system of stochastic differential equations connected by arbitrage arguments between the spot equity market, the index futures and options on index futures. Although various processes for the dynamic of the risk premium may be considered, we motivate and analyse a mean-reverting form. The diffusion part is specified such that the risk premium remains positive. Since the risk premium is not directly observable, information on it is extracted using an unobserved component state space formulation of the system and filtering methodology. As an initial application of the methodology, the results from daily Australian market data from the SFE over a period of twelve months are presented. The small sample properties of the parameter estimates are also examined by bootstrapping the state space system. It is well known in the filtering literature that the estimation of state space system by Kalman filter is sensitive to the specification of the quantities such as initial state variables and the prior covariance matrix. The paper also carries out approximate sensitivity analysis in this respect.