Dependence modeling using mulitvariate copulas with applications - two-day course

Multivariate data abound in many applications including insurance, risk management, finance, biology, health and environmental sciences. Copulas are a useful way to model multivariate data as they account for the dependence structure and provide a flexible representation of the multivariate distribution. They allow for flexible dependence modelling, different from assuming simple linear correlation structures and normality, which makes them particularly well suited to many applications in finance, insurance and medicine, among others.

Course objectives

This two-day short course:

• Introduces and develops the theoretical aspects of dependence modeling with copulas both for continuous and discrete multivariate data.
• Presents real-data applications of multivariate copulas describing features of existing copula software.
• Presents the latest developments both in theory and practice.

Target audience

The course is intended for actuarial practitioners, risk professionals, consultants and academics.