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Pseudo-likelihood estimation in ARCH model

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>06/2006
<mark>Journal</mark>Canadian Journal of Statistics
Issue number2
Number of pages16
Pages (from-to)341-356
<mark>Original language</mark>English


The 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.