This paper discusses a time-series model for daily tax revenues. The model is an unobserved-components model with trend and seasonal components that vary over time. The seasonalities for inter-month and intra-month movements are modelled using stochastic cubic splines. The model is made...

In this paper we explore the forecasting value of historical volatility (extracted from daily return series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of squared high frequency returns within a day). First we consider unobserved...

This paper discusses computationally efficient methods for exact maximum-likelihood estimation of parameters in state-space models. The proposed strategy is based on direct maximisation of the likelihood function, and it can be applied to a wide range of practical univariate and multivariate...