We develop a systematic framework for the joint modelling of returns and multiple daily realised measures. We assume a linear state space representation for the log realised measures, which are noisy and biased estimates of the log integrated variance, at least due to Jensen's inequality. We...

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. By combining existing numerical and Monte Carlo integration methods, we obtain a general and efficient likelihood evaluation method for this class of models. Our approach is based on the idea that only...

The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...

Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

The increasing availability of financial market data at intraday frequencies has not only led to the development of improved volatility measurements but has also inspired research into their potential value as an information source for volatility forecasting. In this paper we explore the...

This discussion paper led to an article in <I>Applied Economics</I> (2013). Vol. 45, pages 3024-3034.<P> The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time...</p></i>

Publication in the 'Journal of Business & Economic Statistics' forthcoming.<A> We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and...</a>

This discussion paper resulted in a publication in the <I>Journal of the Royal Statistical Society Series C</I> (2009). Vol. 58, pages 427-448.<I> Unobserved components time series models decompose a time series into a trend, a season, a cycle, an irregular disturbance, and possibly other components....</i></i>

This discussion paper resulted in an article in the <I>Journal of Financial Econometrics</I> (2012). Vol. 10, pages 354-389.<p> This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and...</p></i>

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...