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 Monte Carlo integration methods. Our methodology explores the idea that...

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...

Estimation using simulation techniques may be very time consuming. Specification tests for structuralstability often require more than one of such computationally demanding estimators. Typically one for thesample, one for the post-sample and one for the combination of sample and post-sample is...