Generalized Additive Modeling for Conditional Copulas

• Activity Number: 26
• Type: Contributed
• Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
• Sponsor: IMS
• Author(s): Valérie Chavez-Demoulin*+
• Companies: University of Lausanne

Abstract

Over the last decades, there has been a growing literature on copula-based models and applications are numerous from economics to quantitative finance, insurance and environmental sciences. The dependence structure between two variables may be influenced by covariates. This motivates the need for introducing a new copula-based approach, using parametric and semi-parametric models. In this work, we propose a generalized additive modelling framework to fit conditional copulas. This framework allows copula-based models to depend on covariates in a parametric, semi-parametric or non-parametric way. The method uses penalized log-likelihoods maximized through specific Newton-Raphson type algorithms. Simulations designed to study the numerical properties of the method indicate that it performs well. Two real datasets are considered as an application. This is a joint work with Thibault Vatter.