We consider representation, estimation and inference on cointegration in a periodic vector autoregressive time series model (PVAR). We show that cointegration amounts to a restriction on a product of parameter matrices. We therefore use GMM to construct estimators of the long-run (cointegration)...

We propose a new approach to tail analysis for data featuring high degrees of leptokurtosis. Heavy tails can typically be found in financial series, like stock returns or durations between trade arrivals. Our method of tail assessment consists in fitting selected pseudo-models to varying subsets...

This paper is concerned with the estimation of cointegrated systems with integrated variables of order greater than 1. Unlike the case of I(1) variables, there are various possibilities of cointegration in the higher order case, which were conveniently formulated in a triangular representation...

This paper is concerned with the Bayesian estimation of non-linear stochastic differential equations when only discrete observations are available. The estimation is carried out using a tuned MCMC method, in particular a blcked Metropolis-Hastings algorithm, by introducing auxiliary points and...