What is Semi-Parametric Copula Estimation

This concept means that the participating marginal distributions are estimated non-parametrically (for example, by the empirical distribution function), while the copula function is estimated parametrically. Initially, this approach was introduced by Chen and Fan (2006) . However, as noted by Patton (in press) , the authors’ useful theoretical results valid for static copulas do not hold for time-varying conditional copulas, and new inference methods should be developed. In addition, the opposite combination of a parametric estimation of the marginal distributions and a non-parametric estimation of the copula also belongs to the semi-parametric copula estimation category (see, e.g., Hafner & Reznikova, 2010 ).

Copula-Based Multivariate Time Series Models

Iva Mihaylova (University of St. Gallen, Switzerland)