Estimation of copula models with discrete margins can be difficult beyond the bivariate case. We show how this can be achieved by augmenting the likelihood with latent variables, and computing inference using the resulting augmented posterior. To evaluate this we propose two efficient Markov...

We propose a multidimensional extension for Patton’s (2006) bi-variate Dynamic Copulas. We also introduce a Dynamic Mixture Copula whose parameters and weights follow well defined dynamic processes. Both approaches improve the Copulas’ flexibilities and their adaptabilities to financial...