Residual analysis for \(\text{ARCH}(p)\)-time series.

DOI10.1007/BF02595704zbMath1109.62351MaRDI QIDQ1872845

Winfried Stute

Publication date: 18 May 2003

Published in: Test (Search for Journal in Brave)

zbMATH Keywords

consistencygoodness-of-fitdistributional convergenceARCH(p)-time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05)

Related Items (11)

Testing Symmetry of the Error Distribution in Nonlinear Heteroscedastic Models ⋮ Residual Empirical Processes and Weighted Sums for Time-Varying Processes with Applications to Testing for Homoscedasticity ⋮ Extended Glivenko–Cantelli theorem and L₁ strong consistency of innovation density estimator for time-varying semiparametric ARCH model ⋮ The \(L_{1}\) strong consistency of ARCH innovation density estimator ⋮ On residual empirical processes of GARCH-SM models: application to conditional symmetry tests ⋮ Extended Glivenko-Cantelli theorem in ARCH\((p)\)-time series ⋮ A functional conditional symmetry test for a GARCH-SM model: Power asymptotic properties ⋮ Asymptotics of $L_\lambda$ -Norms of ARCH(p) Innovation Density Estimators ⋮ Asymptotics for L2-norm of ARCH innovation density estimator ⋮ Asymptotic properties in ARCH(p)-time series ⋮ Adaptiveness of the empirical distribution of residuals in semi-parametric conditional location scale models

Cites Work

• Unnamed Item
• ARCH models and financial applications
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

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