 A flexible extended generalized Pareto distribution for tail estimationPhilémon Gamet and Jonathan Jalbert Environmetrics, 2022, vol. 33, issue 6 Abstract: For both financial and environmental applications, tail distributions often correspond to extreme risks and an accurate modeling is mandatory. The peaks‐over‐threshold model is a classic way to model the exceedances over a high threshold with the generalized Pareto distribution. However, for some applications, the choice of a high threshold is challenging and the asymptotic conditions for using this model are not always satisfied. The class of extended generalized Pareto models can be used in this case. However, the existing extended model have either infinite or null density at the threshold, which is not consistent with tail modeling. In the present article, we propose new extensions of the generalized Pareto distribution for which the density at the threshold is positive and finite. The proposed extensions provide better estimate of the upper tail index for low thresholds than existing models. They are also appropriate for high thresholds because in that case, the extended models simplify to the generalize Pareto model. The performance and flexibility of the models are illustrated with the modeling of temperature exceeding a low threshold and non‐zero precipitations recorded in Montreal. For non‐zero precipitation, the very low threshold of 0 is used. Date: 2022 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:wly:envmet:v:33:y:2022:i:6:n:e2744 Ordering information: This journal article can be ordered from Access Statistics for this article More articles in Environmetrics from John Wiley & Sons, Ltd. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.