Date: 2026-02-13

Time: 15:30-16:30 (Montreal time)

Location: In person, Burnside 1104

https://mcgill.zoom.us/j/81379129957

Meeting ID: 813 7912 9957

Passcode: None

Abstract:

Distorting multivariate distributions is a useful approach for introducing flexibility and capturing model uncertainty. In particular, applying distortions to the copulas representing the underlying dependence structure allows one to generate new, flexible dependence models from existing ones. In this presentation, we investigate the extremal domain of attraction problem for Morillas-type distorted copulas. We establish not only conditions under which such copula-to-copula transformations alter the respective asymptotic behavior, but also discuss conditions under which the distorted copulas remain in the same domain of attraction as the initial undistorted copula. Furthermore, we discuss the effect of these distortions on multivariate risk measures, such as the lower-orthant Value-at-Risk and Range-Value-at-Risk. Finally, we propose a simulation algorithm for Morillas-type distorted copulas, addressing a gap in the literature and providing the means to utilize these modified dependence structures in practice. We end the presentation with an application of distorted copula models for hail insurance.

Speaker

Mélina Mailhot is a professor in the Department of Mathematics and Statistics at Concordia University. She is also director of the Canadian Statistical Sciences Institute in Quebec, and Associate of the Society of Actuaries and the Canadian Institute of Actuaries, where she serves of several different committees. Her research interests include actuarial science, stochastic modeling, risk theory, and applications to insurance and related fields.