Bootstrap refinements for QML estimators of the GARCH(1,1) parameters
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Publication:295411
DOI10.1016/j.jeconom.2008.03.003zbMath1418.62313OpenAlexW2138069662MaRDI QIDQ295411
Valentina Corradi, Emma M. Iglesias
Publication date: 13 June 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2008.03.003
Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Nonparametric statistical resampling methods (62G09)
Related Items (11)
The uncertainty of conditional returns, volatilities and correlations in DCC models ⋮ RESIDUAL-BASED GARCH BOOTSTRAP AND SECOND ORDER ASYMPTOTIC REFINEMENT ⋮ A block bootstrap for quasi-likelihood in sparse functional data ⋮ Valid locally uniform Edgeworth expansions for a class of weakly dependent processes or sequences of smooth transformations ⋮ A residual bootstrap for conditional value-at-risk ⋮ Finite-sample theory and bias correction of maximum likelihood estimators in the EGARCH model ⋮ Tests for \(m\)-dependence based on sample splitting methods ⋮ Volatility filtering in estimation of kurtosis (and variance) ⋮ On the validity of Edgeworth expansions and moment approximations for three indirect inference estimators ⋮ Edgeworth and Moment Approximations: The Case of MM and QML Estimators for the MA(1) Models ⋮ Bootstrap inference on the boundary of the parameter space, with application to conditional volatility models
Cites Work
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- Asymptotic and Bootstrap Inference for AR(∞) Processes with Conditional Heteroskedasticity
- Bootstrap Methods for Markov Processes
- End-of-Sample Instability Tests
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- Bootstrapping Autoregressive Processes with Possible Unit Roots
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