JOURNAL ARTICLE

Pseudo-maximum likelihood estimation of ARCH(infinity) models

Peter M. RobinsonPaolo Zaffaroni

Year: 2008 Journal:   arXiv (Cornell University)   Publisher: Cornell University

Abstract

Strong consistency and asymptotic normality of the Gaussian pseudo maximum likelihood estimate of the parameters in a wide class of ARCH(oo) processes are established. The conditions are shown to hold in case of expo nential and hyperbolic decay in the ARCH weights, though in the latter case a faster decay rate is required for the central limit theorem than for the law of large numbers. Particular parameterizations are discussed.

Keywords:
Mathematics Arch Consistency (knowledge bases) Asymptotic distribution Central limit theorem Maximum likelihood Applied mathematics Exponential family Gaussian Local asymptotic normality Statistics Exponential function Limit (mathematics) Mathematical analysis Estimator Geometry

Metrics

93
Cited By
10.00
FWCI (Field Weighted Citation Impact)
35
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Financial Risk and Volatility Modeling
Social Sciences →  Economics, Econometrics and Finance →  Finance
Market Dynamics and Volatility
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
Statistical Methods and Inference
Physical Sciences →  Mathematics →  Statistics and Probability

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