Geometric ergodicity of nonlinear autoregressive models with changing conditional variances

DOI10.2307/3315968zbMath0958.62081OpenAlexW2089516883MaRDI QIDQ4527902

Min Chen, Gemai Chen

Publication date: 8 April 2001

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/787f08f84cfc21a074042107d4dcf0c8e7dabe11

zbMATH Keywords

momentsgeometric ergodicitystrong mixing propertiesdouble-threshold autoregressive modelsAR(p)-ARCH(p)ARCH(p)

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) General nonlinear regression (62J02)

Related Items (11)

A nonparametric test of conditional autoregressive heteroscedasticity for threshold autoregressive models ⋮ Parametric inference of autoregressive heteroscedastic models with errors in variables ⋮ Nonparametric semirecursive identification in a wide sense of strong mixing processes ⋮ Local linear regression with nonparametrically generated covariates for weakly dependent data ⋮ Extreme values statistics for Markov chains via the (pseudo-) regenerative method ⋮ Empirical likelihood-based subset selection for partially linear autoregressive models ⋮ Mildly explosive autoregression with mixing innovations ⋮ On robust testing for conditional heteroscedasticity in time series models ⋮ Ergodicity and existence of moments for local mixtures of linear autoregressions ⋮ Nonparametric regression for locally stationary time series ⋮ Specification and structural break tests for additive models with applications to realized variance data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Ergodicity of nonlinear first order autoregressive models
• On geometric ergodicity of nonlinear autoregressive models
• On a threshold autoregression with conditional heteroscedastic variances
• The mixing property of bilinear and generalised random coefficient autoregressive models
• Non-linear time series and Markov chains
• RANDOM COEFFICIENT AUTOREGRESSIVE PROCESSES:A MARKOV CHAIN ANALYSIS OF STATIONARITY AND FINITENESS OF MOMENTS
• On the use of the deterministic Lyapunov function for the ergodicity of stochastic difference equations
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

This page was built for publication: Geometric ergodicity of nonlinear autoregressive models with changing conditional variances