A nonparametric sequential test with power 1 for the mean of Lévy-stable laws with infinite variance

DOI10.1007/S11009-006-9749-9zbMath1103.62074OpenAlexW2060018543MaRDI QIDQ861528

Abdelhakim Necir

Publication date: 29 January 2007

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-006-9749-9

zbMATH Keywords

Hill's estimatorLaw of the iterated logarithmAsset returnsHeavy tailsLévy-stable lawSequential test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32) Strong limit theorems (60F15) Sequential statistical analysis (62L10)

Related Items (1)

Estimating the scale parameter of a Lévy-stable distribution via the extreme value approach

Cites Work

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• What portion of the sample makes a partial sum asymptotically stable or normal?
• Strong limit theorems for weighted quantile processes
• The expected sample size of some tests of power one
• A simple general approach to inference about the tail of a distribution
• A nonparametric sequential test with power 1 for the ruin probability in some risk models
• A functional law of the iterated logarithm for kernel-type estimators of the tail index
• Laws of the iterated logarithm for sums of the middle portion of the sample
• Almost sure convergence of the Hill estimator
• Portfolio Analysis in a Stable Paretian Market
• Statistical Methods Related to the Law of the Iterated Logarithm
• Boundary Crossing Probabilities for the Wiener Process and Sample Sums
• Using a bootstrap method to choose the sample fraction in tail index estimation
• Estimating the mean of a heavy tailed distribution

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