Tail characteristics of CRPS-based distributions
J. Roseboom (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Piao Chen – Mentor (TU Delft - Statistics)
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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.