Semilinear copulas

under some suitable assumptions on the generator f . The members of this family have some distinguished features that make them appealing for a variety of situations (presence of a singular component, non-trivial tail dependence, simulating algorithm); moreover, they can be interpreted as the dependence structures arising from a specific stochastic shock model [2, 3, 4]. Some novel statistical inference procedures will be presented [5]. Finally, a possible multivariate generalization will be discussed [6], together with possible applications in risk management [7].