We develop a new class of techniques that takes a copula function and quantifies the dependence properties through a localized coefficient of dependence in the state space. Effectively we develop a numerical procedure to map any copula function to a generalized Gaussian copula function. This...

Let (X1, Y1), … , (Xn, Yn) be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima max( Xi) and max(Yi) is then characterized by the...

In this paper, we study the kernel estimation of the copula density on unit square [0,1]X[0,1], and demonstrate the implementation of this methodology to equity and bond markets. There are two crucial problems associated with this estimator. First, the kernel estimator is biased at the...

We propose a class of flexible non-parametric tests for the presence of dependence between components of a random vector based on weighted Cramér-von Mises functionals of the empirical copula process. The weights act as a tuning parameter and are shown to significantly influence the power of...

Public debates about the rise in top income shares often focus on the growing dispersion in earnings and the soaring pay for top executives and financial-sector employees. But can the change in the marginal distribution of earnings on its own explain the rise in top income shares? Are top...

High levels of carbon emissions and rising income inequality are interconnected challenges for the global society. Commonly-applied linear regression models fail to unravel the complexity of potential bi-directional transmission channels. Specifically, consumption, energy sources and the...