This paper presents a framework for the pricing of contingent claims based on the assumption that the underlying asset has a mixture of transformed normal distributions. Speci...cally, the framework presented (i) can deliver risk neutral contingent claim pricing formulae, (ii) widens the set of distributions used in the mixture by assuming that the terminal price of the underlying security has ...

Non-normal mixture distributions have received increasing attention in recent years. Finite mixtures of multivariate skew-symmetric distributions, in particular, the skew normal and skew t-mixture models, are emerging as promising extensions to the traditional normal and t-mixture models. Most of these parametric families of skew distributions are closely related, and can be classified into fou...

Estimating parameters in a mixture of normal distributions dates back to the 19th century when Pearson originally considered data of crabs from the Bay of Naples. Since then, many real world applications of mixtures have led to various proposed methods for studying similar problems. Among them, maximum likelihood estimation (MLE) and the continuous empirical characteristic function (CECF) metho...

In this paper we present a Bayesian analysis of location-scale regression models assuming standard lifetime distributions and an additional error term with a mixture of normal distributions. Considering a censored lifetime data set, we use Gibbs sampling with Metropolis-Hastings algorithm to get Bayesian quantities of interest. The proposed regression model gives a great flexibility to fit life...