On empirical processes in heteroscedastic time series and their use for hypothesis testing and estimation

zbMath1006.62076MaRDI QIDQ1856544

Mikhaĭl Vasil'evich Boldin

Publication date: 10 February 2003

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

zbMATH Keywords

ARCH modelsresidual empirical processesrobust GM-estimates

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (11)

TESTING FOR A CHANGE OF THE INNOVATION DISTRIBUTION IN AN ARCH MODEL ⋮ On the empirical distribution function of residuals in autoregression with outliers and Pearson's chi-square type tests ⋮ Efficient prediction for linear and nonlinear autoregressive models ⋮ On testing the symmetry of innovation distribution in autoregression schemes ⋮ Residual empirical processes and their application to GM-testing for the autoregression order ⋮ On residual empirical processes of GARCH-SM models: application to conditional symmetry tests ⋮ Statistical estimation errors of VaR under ARCH returns ⋮ The Bickel--Rosenblatt test for diffusion processes ⋮ Two step estimators of the minimum distance type for parameters of the \(\mathrm{ARMA}(1,1)\) model ⋮ Limit results for the empirical process of squared residuals in GARCH models. ⋮ Residual empirical processes and qualitatively robust GM-tests in autoregression

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