Joint and conditional transformed t mixture models with applications to financial and economic data

ABSTRACT We estimate joint and conditional probability densities via a new hybrid;approach that incorporates ideas from copula modeling and makes use of;known analytic results involving the conditional distributions of multivariate;random variables that have joint (usual) multivariate t or t-mixture;distributions. Our method amounts to the application of t or t-mixture;modeling in a special "working space" that is used in copula modeling.;We also provide new simulation algorithms and describe numerical experiments,;performed on accounting data, stock return data and housing price;data, in which we compare the performance of our method with a number;of benchmark approaches.