Tests for structural breaks in memory parameters of long-memory heterogeneous autoregressive models

Eunju Hwang; Dong Wan Shin

doi:10.1080/03610926.2017.1408827

Tests for structural breaks in memory parameters of long-memory heterogeneous autoregressive models

Eunju Hwang, Dong Wan Shin

Department of Statistics

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Tests for structural breaks in the coefficients of the long-memory heterogeneous autoregressive (HAR) models are developed. The tests are based on the partial sum process of the normalized efficient score vector. The tests have the nice property of identifying the parameters of the daily, weekly, and monthly regressors in which breaks occur. Limiting null distributions of the proposed tests are proven to be derived from standard Brownian bridges. A finite sample Monte-Carlo experiment shows reasonable size and power properties of the proposed tests. The proposed method is illustrated by a real data analysis.

Original language	English
Pages (from-to)	5378-5389
Number of pages	12
Journal	Communications in Statistics - Theory and Methods
Volume	47
Issue number	21
DOIs	https://doi.org/10.1080/03610926.2017.1408827
State	Published - 2 Nov 2018

Bibliographical note

Funding Information:
National Research Foundation of Korea (2015-1006133,2016R1A2B4008780) The authors are very grateful for the valuable comments of two anonymous referees which considerably improve the paper.

Publisher Copyright:
© 2018, © 2018 Taylor & Francis Group, LLC.

Keywords

CUSUM
HAR model
long-memory
parameter constancy
realized volatility
structural break

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10.1080/03610926.2017.1408827

Cite this

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abstract = "Tests for structural breaks in the coefficients of the long-memory heterogeneous autoregressive (HAR) models are developed. The tests are based on the partial sum process of the normalized efficient score vector. The tests have the nice property of identifying the parameters of the daily, weekly, and monthly regressors in which breaks occur. Limiting null distributions of the proposed tests are proven to be derived from standard Brownian bridges. A finite sample Monte-Carlo experiment shows reasonable size and power properties of the proposed tests. The proposed method is illustrated by a real data analysis.",

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Tests for structural breaks in memory parameters of long-memory heterogeneous autoregressive models

Abstract

Bibliographical note

Keywords

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