Tail characteristics of CRPS-based distributions

Master thesis (2022)

Authors

J. Roseboom Electrical Engineering, Mathematics and Computer Science

Contributors

P. Chen Statistics - EEMCS (mentor)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Jeroen Roseboom
More Info
expand_more

Published Date

14-01-2022

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In my thesis I researched the potential paths and pitfalls of the newly created ``Taillardat index''.
This index uses the tail characteristics of several CRPS-based distributions to rank forecasters on how well they forecast, with a slight emphasis on extreme events.
From my research I concluded that the ``Taillardat Index'' in its current form is unstable and should be avoided.
Even with theoretical changes, such as moving away from using p-values as a ranking method, the ideas behind the ``Taillardat index'' have to be handled with precaution.
I tried to construct a new index based on the ideas of the paper by Taillardat et al. (2019) and the general theory of forecaster validation, to no avail.
The findings of my endeavours can be found after the reflection of the Taillardat index and in the discussion.

Files

Thesis_Jeroen_Roseboom_Final_V... (pdf)
(pdf | 6.55 Mb)
Unknown license