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Sequential monitoring for changes from stationarity to mild non-stationarity

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Sequential monitoring for changes from stationarity to mild non-stationarity
文献类型:期刊
通讯作者:Liu, ZY (reprint author), Renmin Univ China, Sch Finance, China Financial Policy Res Ctr, Beijing 100872, Peoples R China.
期刊名称:JOURNAL OF ECONOMETRICS影响因子和分区
年:2020
卷:215
期:1
页码:209-238
ISSN:0304-4076
关键词:Change point detection; Stationarity testing; Normal approximation; Non-stationary ARMA time series; Non-stationary GARCH time series
所属部门:财政金融学院
摘要:We develop and study sequential testing procedures a la Chu et at. (1996) for on-line detection of changes in a time series from stationarity to mild forms of non-stationarity. The proposed tests are based on sequential CUSUM and KPSS-type detector processes, and are shown to provide consistent detection under a wide range of change point models, including changes in the parameters of ARMA and GARCH series from values within the model's stationarity parameter region to values close (converging) ...More
We develop and study sequential testing procedures a la Chu et at. (1996) for on-line detection of changes in a time series from stationarity to mild forms of non-stationarity. The proposed tests are based on sequential CUSUM and KPSS-type detector processes, and are shown to provide consistent detection under a wide range of change point models, including changes in the parameters of ARMA and GARCH series from values within the model's stationarity parameter region to values close (converging) to the stationarity boundary. Local asymptotic results are established giving precise descriptions of the time to detection under several of these models, which show that such procedures are powerful to detect a wide range of non-stationary characteristics, including changes in mean, volatility, and unit root behaviour. The proposed methods are investigated by means of a simulation study and in applications to monitoring for changes in trend and unit root behaviour in macroeconomic production series, and to detect changes in volatility of the S&P-500 stock market index. (C) 2019 Elsevier B.V. All rights reserved. ...Hide

DOI:10.1016/j.jeconom.2019.08.010
百度学术:Sequential monitoring for changes from stationarity to mild non-stationarity
语言:外文
基金:Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities; Research Funds of Renmin University of China [17XNQJ01]; Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
作者其他论文



Sequential monitoring for changes from stationarity to mild non-stationarity.Horvath, Lajos, Liu, Zhenya, Rice, Gregory, et al. .JOURNAL OF ECONOMETRICS. 2020, 215(1), 209-238.
The financial integration of China: New evidence on temporally aggregated data for the A-share market.Girardin, Eric;Liu, Zhenya.Conference on Law, Finance and Economic Development.2007,18(3),354-371.
Decoding Chinese stock market returns: Three-state hidden semi-Markov model.Liu, Zhenya;Wang, Shixuan.PACIFIC-BASIN FINANCE JOURNAL.2017,44,127-149.

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