Inference on heavy tails from dependent data
type: Item
instance of: scholarly article
title: Inference on heavy tails from dependent data
zbMATH Open document ID: 1045.62045
published in: Siberian Advances in Mathematics
publication date: 2004-09-06T00:00:00Z
review text: The author deals with problems of tail index and extreme quantile estimation from a sample of dependent random variables. Consistency and asymptotic normality of the corresponding estimators are established under mild mixing conditions. The accuracy of estimation is shown to be of the same order as if the data were independent. An approach to bias reduction is proposed as well as a procedure for practical estimation.
Mathematics Subject Classification ID: 62G32
Mathematics Subject Classification ID: 62G20
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62F10
zbMATH DE Number: 2097080
zbMATH Keywords: tail index
zbMATH Keywords: extreme quantile
zbMATH Keywords: heavy tail
zbMATH Keywords: dependence
zbMATH Keywords: Value-at-Risk
author: S. Yu. Novak
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 2097080