Hybrid Quantile Regression Estimation for Time Series Models with Conditional Heteroscedasticity

DOI10.1111/rssb.12277zbMath1407.62336arXiv1610.07453OpenAlexW2540698443MaRDI QIDQ4628022

Guodong Li, Zhijie Xiao, Yao Zheng, Qian-Qian Zhu

Publication date: 6 March 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1610.07453

zbMATH Keywords

bootstrap methodconditional quantilequantile regressionnonlinear time seriesgeneralized autoregressive conditional heteroscedasticity

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (11)

QUANTILE DOUBLE AUTOREGRESSION ⋮ An Extensive Comparison of Some Well‐Established Value at Risk Methods ⋮ A new generalized exponentially weighted moving average quantile model and its statistical inference ⋮ Bayesian inference for quantile autoregressive model with explanatory variables ⋮ Bootstrapping the transformed goodness-of-fit test on heavy-tailed GARCH models ⋮ Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation ⋮ Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity ⋮ Quantile Estimation of Regression Models with GARCH-X Errors ⋮ Two-step risk analysis in insurance ratemaking ⋮ Adaptiveness of the empirical distribution of residuals in semi-parametric conditional location scale models ⋮ Hybrid quantile estimation for asymmetric power GARCH models

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