Tail behavior and OLS based robust inference in AR-GARCH models

T Lange

doi:10.5705/ss.2009.066

Tail behavior and OLS based robust inference in AR-GARCH models

T Lange

Section of Biostatistics

9 Citations (Scopus)

Abstract

The scope of this paper is twofold. We first describe the tail behavior for general AR-GARCH processes and hence extend the results of Basrak, Davis, and Mikosch (2002b) to another empirical relevant model class. Second, and primarily, we study properties for the OLS estimator in general AR-GARCH model. Specifically it is shown that the OLS estimator of the autoregressive parameter in the AR-GARCH model has a non-standard limiting distribution with a non-standard rate of convergence when the innovations have non-finite fourth order moment.

Original language	English
Journal	Statistica Sinica
Volume	21
Issue number	3
Pages (from-to)	1191-1200
Number of pages	10
ISSN	1017-0405
DOIs	https://doi.org/10.5705/ss.2009.066
Publication status	Published - 2011

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10.5705/ss.2009.066

Cite this

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AB - The scope of this paper is twofold. We first describe the tail behavior for general AR-GARCH processes and hence extend the results of Basrak, Davis, and Mikosch (2002b) to another empirical relevant model class. Second, and primarily, we study properties for the OLS estimator in general AR-GARCH model. Specifically it is shown that the OLS estimator of the autoregressive parameter in the AR-GARCH model has a non-standard limiting distribution with a non-standard rate of convergence when the innovations have non-finite fourth order moment.

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