The multivariate Student-t copula family is used in statistical finance and other areas when there is tail dependence in the data. It often is a good-fitting copula but can be improved on when there is tail asymmetry. Multivariate skew-t copula families can be considered when there is tail dependence and tail asymmetry, and we show how a fast numerical implementation for maximum likelihood esti...

We examine the dependence structure of electricity spot prices across regional markets in the Australian National Electricity Market (NEM). Our analysis is based on a GARCH approach to model the marginal price series in the considered regions in combination with copulae to capture the dependence structure between the different markets. We apply different copula models including Archimedean, ell...

Copula models have become very popular and well studied among the scientific community. Now, most academic researchers, engineers, modelers, etc, own at least some basic copula toolkit and are able to apply it in real situations. Based on the famous Sklar’s theorem (Sklar 1959), copulas allow to put in place the fruitful idea of splitting the specification of a multivariate model into two parts...

The demand for accurate models involving larger numbers of assets is strong not only in view of the financial crisis of 2007-2009. In particular dependencies among assets have not been captured adequately. While standard multivariate copulas have added some flexibility, this flexibility is insufficient in higher dimensional applications. Regular vines can fill this gap by benefiting from the ri...

The complexity of financial products significantly increased in the past ten years. In this paper we investigate the pricing of basket options and more generally of complex exotic contracts depending on multiple indices. Our approach assumes that the underlying assets evolve as dependent GARCH(1,1) processes and it involves to model the dependency among the assets using a copula based on pair-c...

A central aspect of time series analysis is the modeling of dependence over time. Workhorse time series models such as the autoregressive moving average (ARMA) model popularized by Box and Jenkins (1970), the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), or the autoregressive conditional duration (ACD) model of Engle and Russell (...