Testing serial non-independence by self-centring and self-normalizing

DOI10.1080/02331880802506551zbMath1278.60050OpenAlexW2020383923MaRDI QIDQ3396491

Marjorie G. Hahn, Xin-Xin Jiang

Publication date: 18 September 2009

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880802506551

zbMATH Keywords

stationarymixingexchangeableself-normalizationrandom walk modelempirical central limit theoremconditionally mixingself-centringstock daily returns

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Stationary stochastic processes (60G10) Exchangeability for stochastic processes (60G09)

Cites Work

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• On conditionally mixing processes
• The central limit theorem for exchangeable random variables without moments
• When is the Student \(t\)-statistic asymptotically standard normal?
• Dependent central limit theorems and invariance principles
• Empirical central limit theorems for exchangeable random variables
• Testing that marginal sequences of data are not independent via self-normalization
• A Theorem on Products of Random Variables, With Application to Regression

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