Limit results for the empirical process of squared residuals in GARCH models.

DOI10.1016/S0304-4149(03)00004-8zbMath1075.60512OpenAlexW1992342191MaRDI QIDQ2574571

István Berkes, Lajos Horváth

Publication date: 29 November 2005

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4149(03)00004-8

zbMATH Keywords

weak convergenceparameter estimationmartingalesGARCH\((p,q)\)

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional limit theorems; invariance principles (60F17)

Related Items (17)

SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS ⋮ Testing for parameter stability in nonlinear autoregressive models ⋮ Extended Glivenko–Cantelli theorem and L₁ strong consistency of innovation density estimator for time-varying semiparametric ARCH model ⋮ Estimating dynamic copula dependence using intraday data ⋮ A residual bootstrap for conditional value-at-risk ⋮ Testing for bubbles and change-points ⋮ Fitting an error distribution in some heteroscedastic time series models ⋮ Misspecification Testing for the Conditional Distribution Model in GARCH-Type Processes ⋮ Extensions of some classical methods in change point analysis ⋮ On the empirical characteristic function process of the residuals in GARCH models and applications ⋮ Simulation and Estimation of the Meixner Distribution ⋮ Empirical likelihood intervals for conditional Value-at-Risk in ARCH/GARCH models ⋮ Goodness-of-fit test for tail copulas modeled by elliptical copulas ⋮ Testing the equality of error distributions from \(k\) independent GARCH models ⋮ ESTIMATION RISK IN GARCH VaR AND ES ESTIMATES ⋮ Estimating the innovation distribution in nonparametric autoregression ⋮ Adaptiveness of the empirical distribution of residuals in semi-parametric conditional location scale models

Cites Work

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• LARGE SAMPLE DISTRIBUTION OF WEIGHTED SUMS OF ARCH(p) SQUARED RESIDUAL CORRELATIONS
• Non-linear time series and Markov chains
• Testing and estimating change-points in time series
• ON THE SQUARED RESIDUAL AUTOCORRELATIONS IN NON-LINEAR TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY
• Sequential residue empirical processes in the ARCH model
• ON STATIONARITY IN THE ARCH(∞) MODEL
• Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
• Distribution Free Tests of Independence Based on the Sample Distribution Function
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