High-quantile regression for tail-dependent time series

DOI10.1093/BIOMET/ASAA046zbMath1462.62561OpenAlexW3045791433MaRDI QIDQ5857981

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Publication date: 8 April 2021

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/asaa046

zbMATH Keywords

limit theoremdouble asymptoticstail-dependent time seriesadversarial innovationhigh-quantile regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05) Statistics of extreme values; tail inference (62G32) Large deviations (60F10)

Related Items (3)

Rejoinder of “On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures” ⋮ Panel quantile regression for extreme risk ⋮ Tail adversarial stability for regularly varying linear processes and their extensions

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