2018/03/08 by Seyoon Lee, Joseph H.T. Kim · 3 citations
Economics, Econometrics and Finance · Social Sciences · #Financial Risk and Volatility Modeling #Stochastic processes and financial applications #Insurance, Mortality, Demography, Risk Management
paper · doi:10.1080/03610926.2018.1441418
openalex publication_date 2018/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
The GPD is a central distribution in modelling heavy tails in many applications. Applying the GPD to actual datasets however is not trivial. In this paper we propose the Exponentiated GPD (exGPD), created via log-transform of the GPD variable, which has less sample variability. Various distributional quantities of the exGPD are derived analytically. As an application we also propose a new plot based on the exGPD as an alternative to the Hill plot to identify the tail index of heavy tailed datasets, and carry out simulation studies to compare the two.