Yi He & Annika Betken


At Vrije Universiteit Amsterdam

12:00-12:45 Yi He (University of Amsterdam)

Title: Rethinking Tail Inference

Abstract: I will discuss co-authored papers that explore different origins of power laws and demonstrate how they impact the asymptotics of extreme value statistics. Furthermore, I will highlight the interconnected nature of heavy tail phenomena with other important phenomena encountered in economics and finance, such as heterogeneity and approximate sparsity. Recognizing these relationships can enable us to develop more comprehensive solutions to address the challenges of tail inference.

12:45-13:15 Lunch Break

13:15-14:00 Annika Betken (University of Twente)

Title: : Detecting structural changes in the tail-index of long memory stochastic volatility time series

Abstract: We consider a change-point test based on the Hill estimator to test for structural changes in the tail index of long-memory stochastic volatility (LMSV) time series. In order to determine the asymptotic distribution of the corresponding test statistic, we prove a uniform reduction principle for the tail empirical process in a two-parameter Skorohod space. It is shown that such a process displays a dichotomous behavior according to an interplay between the Hurst parameter, i.e. a parameter characterizing the dependence in the data, and the tail index. We will see that, nonetheless, long-memory does not have an influence on the asymptotic behavior of the test statistic.