Date: 2012-11-09

Time: 14:30-15:30

Location: BURN 1205

Abstract:

Assessing tail risks using the asymptotic models provided by multivariate extreme value theory has the danger that when asymptotic independence is present (as with the Gaussian copula model), the asymptotic model provides estimates of probabilities of joint tail regions that are zero. In diverse applications such as finance, telecommunications, insurance and environmental science, it may be difficult to believe in the absence of risk contagion. This problem can be partly ameliorated by using hidden regular variation which assumes a lower order asymptotic behavior on a subcone of the state space and this theory can be made more flexible by extensions in the following directions: (i) higher dimensions than two; (ii) where the lower order variation on a subcone is of extreme value type different from regular variation; and (iii) where the concept is extended to searching for lower order behavior on the complement of the support of the limit measure of regular variation. We discuss some challenges and potential applications to this ongoing effort.

Speaker

Sidney Resnick is the Lee Teng Hui Professor in Engineering at the School of Operations Research and Information Engineering, Cornell University. He is the author of several well-known textbooks in probability and extreme-value theory.