Comparison of the several parameterized estimators for the positive extreme value index

ABSTRACT

In the paper we compare several parameterized estimators for the positive extreme value index, which is a very important parameter appearing in the estimation of the probability of rare events. Firstly, asymptotic comparison at optimal levels of the corresponding tail index estimators is performed. Secondly, the practical validation of asymptotic results for moderate finite samples is done by means of Monte-Carlo simulations. We demonstrate that theoretical domination of the positive extreme value index estimators, which are asymptotically normal with a null asymptotic bias, is not reflected in Monte-Carlo simulations. Moreover, the estimators of such type do not demonstrate stability in the sense of empirical mean-squared error.

KEYWORDS:

• Asymptotic normality
• tail index estimation
• parameterized estimators
• regularly varying function

AMS SUBJECT CLASSIFICATION:

• 62F12
• 62G32
• 60F05

Disclosure statement

No potential conflict of interest was reported by the authors.