Robust and efficient estimation of GARCH models based on Hellinger distance

DOI10.1080/02664763.2021.1970120OpenAlexW3198220203MaRDI QIDQ5044704

Liang Chen, Jingjing Wu, Qiang Zhao

Publication date: 2 November 2022

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

Full work available at URL: https://doi.org/10.1080/02664763.2021.1970120

zbMATH Keywords

robustnessmaximum likelihood estimationkernel estimationGARCH modelsminimum (profile) Hellinger distance estimation

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric robustness (62G35) Nonparametric estimation (62G05) Point estimation (62F10) Applications of statistics (62Pxx)

Cites Work

• Efficient Hellinger distance estimates for semiparametric models
• Minimum distance estimation of GARCH(1,1) models
• Minimum Hellinger distance estimates for parametric models
• Efficiency versus robustness: The case for minimum Hellinger distance and related methods
• The ``automatic robustness of minimum distance functionals
• Estimation of GARCH Models from the Autocorrelations of the Squares of a Process
• RANK-BASED ESTIMATION FOR GARCH PROCESSES
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Profile Hellinger distance estimation
• On minimum Hellinger distance estimation
• Alternatives to the Median Absolute Deviation
• Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
• Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• GARCH Model Estimation Using Estimated Quadratic Variation

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