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Asymptotically Efficient Estimation of the Change Point for Semiparametric GARCH models Author info | Abstract | Publisher info | Download info | Related research | Statistics Takayuki Shiohama
Instability of volatility parameters in GARCH models in an important issue for analyzing financial time series. In this paper we investigate the asymptotic theory for change point estimators in semiparametric GARCH models. When the parameters of a GARCH models have changed within an observed realization, two types estimators, Maximum likelihood estimator (MLE) and Bayesian estimator (BE), are proposed. Then we derive the asymptotic distributions for these estimators. The MLE and BE have different limit laws, and the BE is asymptotically efficient. Monte Carlo studies on the finite sample behaviors are conducted.
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Paper provided by Institute of Economic Research, Hitotsubashi University in its series Discussion Paper Series with number
a471.
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Date of creation: Jan 2006Date of revision:
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Keywords: GARCH process ; change point ; maximum likelihood estimator ; Bayesian estimator ; asymptotic efficiency ; Other versions of this item:
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