Note on bandwidth selection in testing for long range dependence.
type: Item
instance of: scholarly article
title: Note on bandwidth selection in testing for long range dependence.
zbMATH Open document ID: 1036.91044
DOI: 10.1016/S0165-1765(02)00180-5
author: Zhijie Xiao
published in: Economics Letters
publication date: 2003-01-22T00:00:00Z
review text: Many tests for \(I(0)\) versus \(I(d)\) processes are standardized by long-run variance estimators, which are estimated by nonparametric methods that entail a choice of bandwidth. Data-dependent bandwidth choices using plug-in methods have been suggested and used in many applications. In a recent paper, \textit{V. Teverovsky}, \textit{M. S. Taqqu} and \textit{W. Willinger} [J. Stat. Plann. Inference 80, 211--227 (1999; Zbl 1044.60508)] conducted a Monte Carlo study on the modified rescaled range (R/S) test and found that the test ``has a strong bias towards accepting the null hypothesis''. In this note, we show that the Monte Carlo finding of unusually low power and the empirical finding of short-memory in stock returns indexes are related to the data-dependent bandwidth choice. Simply using the data-dependent bandwidth choice is inappropriate.
Mathematics Subject Classification ID: 91B82
zbMATH DE Number: 1857191
zbMATH Keywords: Bandwidth selection
zbMATH Keywords: Integrated process
zbMATH Keywords: Long-memory process
zbMATH Keywords: Nonparametric
zbMATH Keywords: Semiparametric
describes a project that uses: longmemo
MaRDI profile type: Publication
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full work available at URL: s0165-1765(02)00180-5
OpenAlex ID: W2003311125
description: scientific article; zbMATH DE number 1857191