A bivariate normal distribution, with the attendant non-analytically integrable p.d.f., lies at the hearts of many financial theories. Its derived Gaussian copula ostensibly does away with the normality assumptions, only to retain the linear (Pearson's) correlation measure implicit to said...

The inability of the Gaussian copula to describe the tail dependence among risks has been sharply criticized since the 2008 financial crisis. In this paper, we extend the classic Gaussian copula to the distorted GAB copula with the distorted mix method. Similar with the Gaussian copula, the...

For multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically effi cient estimator is proposed for the Euclidean copula parameter. This estimator is defined as a one-step update of a rank-based pilot estimator in the direction...