We provide a Bayesian analysis of pair-copula constructions (PCCs) (Aas et al., 2009), which outperform many other multivariate copula constructions in modeling dependencies in financial data. We use bivariate t-copulas as building blocks in a PCC to allow extreme events in bivariate margins...

In this paper we introduce an ACD-ECOGARCH(1,1) model. An exponential autoregressive conditional duration model is used to describe the dependence structure in durations of ultra-high-frequency financial data. The innovation process of the ACD model then defines the interarrival times of a...

We consider distributional free inference to test for positive quadrant dependence, that is, for the probability that two variables are simultaneously small (or large) being at least as great as it would be were they dependent. Tests for its generalization to higher dimensions, namely positive...