Pseudo‐likelihood estimation in ARCH models
Copyright policy )Pseudo‐likelihood estimation in ARCH models
AbstractThe author presents asymptotic results for the class of pseudo‐likelihood estimators in the autoregressive conditional heteroscedastic models introduced by Engle (1982). Unlike what is required for the quasi‐likelihood estimator, some estimators in the class he considers do not require the finiteness of the fourth moment of the error density. Thus his method is applicable to heavy‐tailed error distributions for which moments higher than two may not exist.
- Lancaster University United Kingdom
- University of Liverpool United Kingdom
Time series, auto-correlation, regression, etc. in statistics (GARCH), Asymptotic distribution theory in statistics, Computational problems in statistics, 310, Asymptotic properties of parametric estimators, 510
Time series, auto-correlation, regression, etc. in statistics (GARCH), Asymptotic distribution theory in statistics, Computational problems in statistics, 310, Asymptotic properties of parametric estimators, 510
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