Tail behavior and OLS based robust inference in AR-GARCH models
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Tail behavior and OLS based robust inference in AR-GARCH models. / Lange, T.
In: Statistica Sinica, Vol. 21, No. 3, 2011, p. 1191-1200.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Tail behavior and OLS based robust inference in AR-GARCH models
AU - Lange, T
PY - 2011
Y1 - 2011
N2 - 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.
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.
U2 - 10.5705/ss.2009.066
DO - 10.5705/ss.2009.066
M3 - Journal article
VL - 21
SP - 1191
EP - 1200
JO - Statistica Sinica
JF - Statistica Sinica
SN - 1017-0405
IS - 3
ER -
ID: 33248716