A conditional least squares approach to PGARCH and PARMA-PGARCH time series estimation

DOI10.1016/j.crma.2010.10.019zbMath1202.62110OpenAlexW1969940256MaRDI QIDQ611171

Ines Lescheb, Abdelouahab Bibi

Publication date: 14 December 2010

Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.crma.2010.10.019

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

Probabilistic properties of a Markov-switching periodic GARCH process ⋮ Estimation and Asymptotic Properties in PeriodicGARCH(1, 1) Models ⋮ Estimation for periodic ARMA models with unspecified noises

Cites Work

• Estimating linear representations of nonlinear processes
• Strong consistency and asymptotic normality of least squares estimators for PGARCH and PARMA-PGARCH models
• On periodic and multiple autoregressions
• Large Sample Properties of Parameter Estimates for Periodic ARMA Models
• Quasi-maximum likelihood estimation of periodic GARCH and periodic ARMA-GARCH processes

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