Modeling high dimensional asset pricing returns using a dynamic skewed copula model

Abstract

We propose a dynamic skewed copula to model multivariate dependence in asset returns in a flexible yet parsimonious way. We then apply the model to 50 exchange-traded funds. The new copula is shown to have better in-sample and out-of-sample performance than existing copulas. In particular, the dynamic model is able to capture increasing dependence patterns during financial crisis periods. It is crucial for investors to take dynamic dependence structure into account when modeling high dimensional returns.