Bounds on Some Entropy Risk Measures for Finite Mixtures of Multivariate Skew-t Distributions

Abstract

Entropy is a risk measure which has played an important role in quantity of information losses. Also entropy applications have been developed in mixture models. In this paper, we consider a class of skew-t mixture models. Upper and lower bounds for Shannon, Renyi, Tsallis and Verma entropies are found for this model. Then simulation studies are examined on the financial data set.