  The multivariate version of the Mixed Tempered Stable is proposed. It is a
generalization of the Normal Variance Mean Mixtures. Characteristics of this
new distribution and its capacity in fitting tails and capturing dependence
structure between components are investigated. We discuss a random number
generating procedure and introduce an estimation methodology based on the
minimization of a distance between empirical and theoretical characteristic
functions. Asymptotic tail behavior of the univariate Mixed Tempered Stable is
exploited in the estimation procedure in order to obtain a better model
fitting. Advantages of the multivariate Mixed Tempered Stable distribution are
discussed and illustrated via simulation study.
