Semiparametric estimation of the intensity of long memory in conditional heteroskedasticity

The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model proposed by Giraitis, Robinson and Surgailis (1999). We consider methods based on the partial sums of the squared observations which are similar in spirit to the classical R/S analysis as well as spectral domain approximate maximum likelihood estimators. The finite sample performance of the estimators is examined by means of a Monte Carlo study.

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Year of publication:	1999
Authors:	Giraitis, Liudas ; Kokoszka, Piotr ; Leipus, Remigijus ; Teyssière, Gilles
Institutions:	Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät
Subject:	long memory \| ARCH models \| semiparametric estimation \| modified R/S \| KPSS and V/S statistics \| periodogram

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Extent:	application/pdf
Series:	SFB 373 Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 1999,81
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010956357