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자연과학대학
통계학전공
Journal papers
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Stationary bootstrapping for structural break tests for a heterogeneous autoregressive model
Title
Stationary bootstrapping for structural break tests for a heterogeneous autoregressive model
Authors
Hwang E.
;
Shin D.W.
Ewha Authors
신동완
SCOPUS Author ID
신동완
Issue Date
2017
Journal Title
Communications for Statistical Applications and Methods
ISSN
2287-7843
Citation
Communications for Statistical Applications and Methods vol. 24, no. 4, pp. 367 - 382
Keywords
CUSUM test
;
Heterogeneous autoregressive(∞) model
;
Stationary bootstrap
;
Structural changes
Publisher
Korean Statistical Society
Indexed
SCOPUS; KCI
Document Type
Article
Abstract
We consider an infinite-order long-memory heterogeneous autoregressive (HAR) model, which is motivated by a long-memory property of realized volatilities (RVs), as an extension of the finite order HAR-RV model. We develop bootstrap tests for structural mean or variance changes in the infinite-order HAR model via stationary bootstrapping. A functional central limit theorem is proved for stationary bootstrap sample, which enables us to develop stationary bootstrap cumulative sum (CUSUM) tests: a bootstrap test for mean break and a bootstrap test for variance break. Consistencies of the bootstrap null distributions of the CUSUM tests are proved. Consistencies of the bootstrap CUSUM tests are also proved under alternative hypotheses of mean or variance changes. A Monte-Carlo simulation shows that stationary bootstrapping improves the sizes of existing tests. © 2017 The Korean Statistical Society, and Korean International Statistical Society.
DOI
10.5351/CSAM.2017.24.4.367
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