Title

Nonparametric Estimation Of Structural Change Points In Volatility Models For Time Series

Keywords

Asymptotic properties; Change points in volatility; Least squares; Nonparametric estimation

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. © 2004 Elsevier B.V. All rights reserved.

Publication Date

5-1-2005

Publication Title

Journal of Econometrics

Volume

126

Issue

1

Number of Pages

79-114

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jeconom.2004.02.008

Socpus ID

10444236487 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/10444236487

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