Port-Estimation of a Shape Second-Order Parameter

Abstract

In this paper we study, under a semi-parametric framework and for heavy right tails, a class of location invariant estimators of a shape second-order parameter, ruling the rate of convergence of the normalised sequence of maximum values to a non-degenerate limit. This class is based on the PORT methodology, with PORT standing for peaks over random thresholds. Asymptotic normality of such estimators is achieved under a third-order condition on the right-tail of the underlying model F and for suitable large intermediate ranks. An illustration of the finite sample behaviour of the estimators is provided through a small-scale Monte-Carlo simulation study.

Keywords

• asymptotic properties
• location/scale invariant estimation
• Monte-Carlo simulation
• PORT methodology
• sample of excesses
• semi-parametric estimation