Multivariate Dependence Analysis via Tree Copula Models: an Application to One-year Forward Energy Contracts

We propose a novel multivariate approach for dependence analysis in the energy market. The methodology is based on tree copulas and GARCH type processes. We use it to study the dependence structure among the main factors affecting energy price, and to perform portfolio risk evaluation. The temporal dynamic of the examined variables is described via a set of GARCH type models where the joint distribution of the standardised residuals is represented via suitable tree copula structures. Working in a Bayesian framework, we perform both qualitative and quantitative learning. Posterior summaries of the quantities of interest are obtained via MCMC methods.