This paper provides a general methodology for testing for dependence in time series data, with particular emphasis given to non-Gaussian data. A dynamic model is postulated for a continuous latent variable and the dynamic structure transferred to the non-Gaussian, possibly discrete,...

A general Bayesian Markov Chain Monte Carlo methodology is utilized for conducting an analysis of the intensity process of stock market data. The sampling scheme employed is a hybrid of the Gibbs and Metropolis Hastings algorithms. Both duration and count data time series approaches are utilized...