Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28713
Title: Nonparametric estimation of structural change points in volatility models for time series
Authors: Chen, G
Choi, YK
Zhou, Y
Keywords: Asymptotic properties
Change points in volatility
Least squares
Nonparametric estimation
Issue Date: 2005
Publisher: North-Holland
Source: Journal of econometrics, 2005, v. 126, no. 1, p. 79-114 How to cite?
Journal: Journal of econometrics 
Abstract: We propose a hybrid estimation procedure that combines the least squares and nonparametric methods to estimate change points of volatility in time series models. Its main advantage is that it does not require any specific form of marginal or transitional densities of the process. We also establish the asymptotic properties of the estimators when the regression and conditional volatility functions are not known. The proposed tests for change points of volatility are shown to be consistent and more powerful than the nonparametric ones in the literature. Finally, we provide simulations and empirical results using the Hong Kong stock market index (HSI) series.
URI: http://hdl.handle.net/10397/28713
ISSN: 0304-4076
EISSN: 1872-6895
DOI: 10.1016/j.jeconom.2004.02.008
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