We present a non-parametric tail dependence estimator which arises naturally from a specific regression model. Above that, this tail dependence estimator also results from a specific copula mixture. -- Upper tail dependence ; nonparametric estimation ; copula

We present a new family of copulas ("generalized mean copulas") which is positive comprehensive and allows for upper tail dependence. It includes the Spearman copula and a specific Fréchet copula as special cases. Some properties and a generalized tail dependence estimator are derived. Finally,...

This chapter is concerned with the problem of quantile prediction (or forecasting). There are numerous applications in economics and finance where quantiles are of interest. We primarily focus on methods that are relevant for dynamic time series data. The chapter is organized around two key...