New approximation for GARCH parameters estimate

2017/03/08 by Yakoub Boularouk, Boularouk, Yakoub, Nasr-Eddine Hamri +2
Computer Science · Economics, Econometrics and Finance · Environmental Science · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Hydrology and Drought Analysis #Image and Signal Denoising Methods #stat.CO

paper · pdf · doi:10.48550/arxiv.1703.03004

10 pages, 4 tables, 3 figures

openalex publication_date 2017/03/08 · arxiv created 2017/03/10 · arxiv updated 2017/03/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper presents a new approach for the optimization of GARCH parameters estimation. Firstly, we propose a method for the localization of the maximum. Thereafter, using the methods of least squares, we make a local approximation for the projection of the likelihood function curve on two dimensional planes by a polynomial of order two which will be used to calculate an estimation of the maximum.

Citations

• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Function minimization by conjugate gradients
• A family of variable-metric methods derived by variational means
• A new approach to variable metric algorithms
• A Simplex Method for Function Minimization

Related

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• R-estimators in GARCH models; asymptotics, applications and bootstrapping
• Non-Gaussian Quasi Maximum Likelihood Estimation of GARCH Models
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• Maximum Likelihood Estimation for Linear Gaussian Covariance Models