We study the possibility for international diversification of catastrophe risk by the insurance sector. Adopting the argument that large insurance losses may be a `globalizing factor' for the industry, we study the dependence of geographically distant insurance markets via equity returns. In...

The multivariate analysis of a panel of economic and financial time series with mixed frequencies is a challenging problem. The standard solution is to analyze the mix of monthly and quarterly time series jointly by means of a multivariate dynamic model with a monthly time index: artificial...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

This discussion paper led to a publication in <A href="http://www.sciencedirect.com/science/article/pii/S0167947304001562">'Computational Statistics & Data Analysis'</A>, 49(2), 417-44.<P>We examine the asymptotic efficiency of OLS and IV estimators in a simple dynamic structural model with a constant and two explanatory variables: the lagged dependent variable and an...</p></a>

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...

This discussion paper led to a publication in the <I>Journal of Applied Econometrics</A>. Vol. 19, issue 5, pages 611-636.<P> Convergence in gross domestic product series of five European countriesis empirically identified using multivariate time series models that arebased on unobserved components with...</p></i>

This version has replaced the version of January 30, 2012.<P> A successful construction of an importance density for nonlinear non-Gaussian state space models is crucial when Monte Carlo simulation methods are used for likelihood evaluation, signal extraction of dynamic latent factors and...</p>

Accepted by the <Journal of Empirical Finance</I>.<P> We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated) dynamics and heavy-tailed densities. Our new multivariate model accounts for typical empirical features in financial time series while being robust to...</p></journal>

We investigate the intraday dependence pattern between tick data of stock price changes using a new time-varying model for discrete copulas. We let parameters of both the marginal models and the copula vary over time using an observation driven autoregressive updating scheme based on the score...

The failure to describe the time series behaviour of most realexchange rates as temporary deviations from fixedlong-term means may be due to time variation of the equilibriathemselves, see Engel (2000). We implement thisidea using an unobserved components model and decompose theobservations on...