Inference for the tail index of a GARCH(1,1) model and an AR(1) model with ARCH(1) errors
From MaRDI portal
Publication:5860900
DOI10.1080/07474938.2016.1224024zbMath1490.62286OpenAlexW2511532413MaRDI QIDQ5860900
Chenxue Li, Rong Mao Zhang, Liang Peng
Publication date: 4 March 2022
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07474938.2016.1224024
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistics of extreme values; tail inference (62G32)
Related Items (5)
TEST FOR ZERO MEDIAN OF ERRORS IN AN ARMA–GARCH MODEL ⋮ MCMC interweaving strategy for estimating stochastic volatility model and its application ⋮ On a Partially Non-Stationary Vector AR Model with Vector GARCH Noises: Estimation and Testing ⋮ Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference ⋮ Empirical likelihood test for the application of swqmele in fitting an arma‐garch model
Cites Work
- Unnamed Item
- Empirical likelihood ratio confidence regions
- Implicit renewal theory and tails of solutions of random equations
- GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference
- Limit theory for moving averages of random variables with regularly varying tail probabilities
- Limit theory for the sample covariance and correlation functions of moving averages
- On tail index estimation using dependent data
- Random difference equations and renewal theory for products of random matrices
- A simple general approach to inference about the tail of a distribution
- Tail index estimation for dependent data
- Empirical likelihood and general estimating equations
- Limit theory for bilinear processes with heavy-tailed noise
- 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
- Regular variation of GARCH processes.
- The sample autocorrelations of heavy-tailed processes with applications to ARCH
- Extremal behaviour of solutions to a stochastic difference equation with applications to ARCH processes
- Limit theory for the sample autocorrelations and extremes of a GARCH \((1,1)\) process.
- Nonlinear time series. Nonparametric and parametric methods
- The tail of the stationary distribution of an autoregressive process with \(\text{ARCH}(1)\) errors
- Weighted approximations of tail processes for \(\beta\)-mixing random variables.
- Hill's estimator for the tail index of an ARMA model
- The efficiency of the estimators of the parameters in GARCH processes.
- Interval estimation of the tail index of a GARCH(1,1) model
- Robust estimation and inference for heavy tailed GARCH
- Structural Change Tests in Tail Behaviour and the Asian Crisis
- Least absolute deviations estimation for ARCH and GARCH models
- Tail behavior and OLS estimation in AR-GARCH models
- ASYMPTOTIC INFERENCE FOR AR MODELS WITH HEAVY-TAILED G-GARCH NOISES
- Asymptotic behavior of hill's estimator for autoregressive data
- Sample correlation behavior for the heavy tailed general bilinear process
- ESTIMATION OF THE MAXIMAL MOMENT EXPONENT OF A GARCH(1,1) SEQUENCE
- Estimation and Testing Stationarity for Double-Autoregressive Models
- TAIL INDEX OF AN AR(1) MODEL WITH ARCH(1) ERRORS
- LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises
- Inference in Arch and Garch Models with Heavy-Tailed Errors
- Weighted least absolute deviations estimation for an AR(1) process with ARCH(1) errors
This page was built for publication: Inference for the tail index of a GARCH(1,1) model and an AR(1) model with ARCH(1) errors