Semiparametric efficient adaptive estimation of asymmetric GARCH models |
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Authors: | Yiguo Sun Thanasis Stengos |
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Institution: | Department of Economics, University of Guelph, Guelph, Ont., Canada N1G 2W1 |
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Abstract: | In this paper we derive a semiparametric efficient adaptive estimator of an asymmetric GARCH model. Applying some general results from Drost et al. 1997. The Annals of Statistics 25, 786–818], we first estimate the unknown density function of the disturbances by kernel methods, then apply a one-step Newton–Raphson method to obtain a more efficient estimator than the quasi-maximum likelihood estimator. The proposed semiparametric estimator is adaptive for parameters appearing in the conditional standard deviation model with respect to the unknown distribution of the disturbances. |
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Keywords: | C14 C22 |
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