M-ESTIMATION IN GARCH MODELS

DOI10.1017/S0266466608080602zbMath1277.62200OpenAlexW2117007602MaRDI QIDQ3551008

Kanchan Mukherjee

Publication date: 8 April 2010

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

Full work available at URL: https://doi.org/10.1017/s0266466608080602

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09)

Related Items (8)

RANK-BASED ESTIMATION FOR GARCH PROCESSES ⋮ Mallows' quasi-likelihood estimation for log-linear Poisson autoregressions ⋮ M-estimation for periodic GARCH model with high-frequency data ⋮ Robust estimation for Poisson integer-valued GARCH models using a new hybrid loss ⋮ Diagnostic Checking for GARCH-Type Models ⋮ Robust \(M\)-estimate of GJR model with high frequency data ⋮ Robust estimation methods for a class of log-linear count time series models ⋮ Robust quasi-likelihood estimation for the negative binomial integer-valued GARCH(1,1) model with an application to transaction counts

Uses Software

• FinTS

Cites Work

• Unnamed Item
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• Stationarity of GARCH processes and of some nonnegative time series
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• Generalized autoregressive conditional heteroscedasticity
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• Pseudo-maximum likelihood estimation of \(\text{ARCH}(\infty)\) models
• Least absolute deviations estimation for ARCH and GARCH models
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models
• Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
• STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREM
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• Analysis of Financial Time Series

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