TAIL INDEX OF AN AR(1) MODEL WITH ARCH(1) ERRORS

DOI10.1017/S0266466612000801zbMath1290.62071OpenAlexW2120508818MaRDI QIDQ4979320

Deyuan Li, Ngai Hang Chan, Rong Mao Zhang, Liang Peng

Publication date: 20 June 2014

Published in: Econometric Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s0266466612000801

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Extreme value theory; extremal stochastic processes (60G70)

Related Items (5)

Empirical likelihood inference for INAR(1) model with explanatory variables ⋮ CHANGE POINT TESTS FOR THE TAIL INDEX OFβ-MIXING RANDOM VARIABLES ⋮ Multivariate autoregressive extreme value process and its application for modeling the time series properties of the extreme daily asset prices ⋮ Empirical likelihood for linear and log-linear INGARCH models ⋮ Inference for the tail index of a GARCH(1,1) model and an AR(1) model with ARCH(1) errors

Cites Work

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• A review on empirical likelihood methods for regression
• Empirical likelihood ratio confidence regions
• Empirical likelihood and general estimating equations
• Asymptotic behaviour of the sample autocovariance and autocorrelation function of the \(AR(1)\) process with \(\text{ARCH}(1)\) errors
• Extremal behavior of the autoregressive process with ARCH(1) errors
• Limit theory for the sample autocorrelations and extremes of a GARCH \((1,1)\) process.
• The tail of the stationary distribution of an autoregressive process with \(\text{ARCH}(1)\) errors
• Estimation and Testing Stationarity for Double-Autoregressive Models
• Weighted least absolute deviations estimation for an AR(1) process with ARCH(1) errors

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