Least absolute deviations estimation for ARCH and GARCH models

Peng, Liang and Yao, Qiwei ORCID: 0000-0003-2065-8486 (2003) Least absolute deviations estimation for ARCH and GARCH models. Biometrika, 90 (4). pp. 967-975. ISSN 0006-3444

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Abstract

Hall & Yao (2003) showed that, for ARCH/GARCH, i.e. autoregressive conditional heteroscedastic/generalised autoregressive conditional heteroscedastic, models with heavy‐tailed errors, the conventional maximum quasilikelihood estimator suffers from complex limit distributions and slow convergence rates. In this paper three types of absolute deviations estimator have been examined, and the one based on logarithmic transformation turns out to be particularly appealing. We have shown that this estimator is asymptotically normal and unbiased. Furthermore it enjoys the standard convergence rate of n1/2 regardless of whether the errors are heavy‐tailed or not. Simulation lends further support to our theoretical results.

Item Type:	Article
Official URL:	http://biomet.oxfordjournals.org/
Additional Information:	© 2003 Biometrika Trust
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	20 Jun 2008 09:00
Last Modified:	01 Oct 2024 03:31
URI:	http://eprints.lse.ac.uk/id/eprint/5828

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