Canadian
Mathematical
Society
Krieger-Nelson Prize Winner
Dr. Johanna G. Nešlehová
McGill University
Dr. Nešlehová is a world leader on copula models and their many ramifications in multivariate statistics, notably in relation to risk analysis and extreme-value theory, an area to which she has made numerous outstanding contributions. She is well-known for promoting statistical risk analysis in insurance and finance through her writing and through short courses. She has also made key contributions to the theory of empirical processes and has wide-ranging interests in the application of stochastic dependence and extreme values to climate and finance. In 2019, Dr. Nešlehová was the distinguished recipient of the CRM-SSC Prize in Statistics.
Extreme or Not Extreme: The Intricacies and Challenges of Rare Event Modeling
Sunday, June 4: 13:30-14:30
STEM 224
Accounting for dependence between rare events such as severe storms, floods, or large financial losses is essential for sound risk management. This can be accomplished very effectively by combining extreme-value theory with copula modeling, and by relying on the component-wise ranks of multivariate data to make inference. I will first explain how copulas can adequately capture the dependence between extreme events when the commonly used asymptotic extreme-value models are unsuitable. As extending these ideas to a large collection of risks calls for hierarchical models, I will next show how their structure might be inferred by identifying patterns in large-scale rank correlation matrices. Finally, I will use some of these techniques to explore the behavior of the largest claim size in a portfolio of possibly dependent insurance claims.