A0417
Title: Conditional extreme value estimation for dependent time series
Authors: Theodor Henningsen - University of Copenhagen (Denmark) [presenting]
Martin Bladt - University of Copenhagen (Denmark)
Laurits Glargaard - University of Copenhagen (Denmark)
Abstract: The consistency and weak convergence of the conditional tail function and conditional Hill estimators is studied under broad dependence assumptions for a heavy-tailed response sequence and a covariate sequence. Consistency is established under alpha-mixing, while asymptotic normality follows from beta-mixing and second-order conditions. A key aspect of the approach is its versatile functional formulation in terms of the conditional tail process. Simulations demonstrate its performance across dependence scenarios. The method is applied to extreme event modeling in the oil industry, revealing distinct tail behaviors under varying conditioning values.
