A novel class of interacting Markov chain Monte Carlo (MCMC) algorithms, hereby referred to as the Parallel Hierarchical Sampler (PHS), is developed and its mixing properties are assessed. PHS algorithms are modular MCMC samplers designed to produce reliable estimates for multi-modal and...

It is well known that financial returns are usually not normally distributed, but rather exhibit excess kurtosis. This implies that there is greater probability mass at the tails of the marginal or conditional distribution. Mixture-type time series models are potentially useful for modeling...

Multivariate mode hunting is of increasing practical importance. Only a few such methods exist, however, and there usually is a trade-off between practical feasibility and theoretical justification. In this paper we attempt to do both. We propose a method for locating isolated modes (or better,...