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Sid Resnick: Exploring Dependence in Multivariate Heavy Tailed Data

Time: Mon 2019-09-16 15.15

Location: Room F11, Lindstedtsvägen 22

Lecturer: Sid Resnick, Cornell University

Abstract: We review a framework for considering multivariate data that could plausibly come from a multivariate power law. The framework is flexible enough to allow for multiple (even infinite) heavy tail regimes depending on the choice of scaling and the definition of an extreme region. We use the framework to explore extremal dependence between components using both graphical and analytical means. An example using market returns is given for what we call "strong dependence" and an exploratory graph technique can highlight the most dependent components.

(Joint seminar with Mathematical Statistics)

Belongs to: Department of Mathematics
Last changed: Sep 09, 2019