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Testing for Change-Points in Long-Range Dependent Time Series by Means of a Self-Normalized Wilcoxon Test

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  • Annika Betken

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  • Annika Betken, 2016. "Testing for Change-Points in Long-Range Dependent Time Series by Means of a Self-Normalized Wilcoxon Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 785-809, November.
    • Handle: RePEc:bla:jtsera:v:37:y:2016:i:6:p:785-809
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    References listed on IDEAS

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    1. Lobato I. N., 2001. "Testing That a Dependent Process Is Uncorrelated," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1066-1076, September.
    2. Jaromír Antoch & Marie Hušková & Alicja Janic & Teresa Ledwina, 2008. "Data driven rank test for the change point problem," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(1), pages 1-15, June.
    3. Shao, Xiaofeng & Zhang, Xianyang, 2010. "Testing for Change Points in Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1228-1240.
    4. Robinson, Peter M., 2014. "The estimation of misspecified long memory models," Journal of Econometrics, Elsevier, vol. 178(P2), pages 225-230.
    5. Yixiao Sun & Peter C. B. Phillips & Sainan Jin, 2008. "Optimal Bandwidth Selection in Heteroskedasticity-Autocorrelation Robust Testing," Econometrica, Econometric Society, vol. 76(1), pages 175-194, January.
    6. Marc Henry, 2001. "Robust Automatic Bandwidth for Long Memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(3), pages 293-316, May.
    7. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    8. Xiaofeng Shao, 2011. "A simple test of changes in mean in the possible presence of long‐range dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 598-606, November.
    9. Robinson, Peter M., 2014. "The estimation of misspecified long memory models," LSE Research Online Documents on Economics 53692, London School of Economics and Political Science, LSE Library.
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    Cited by:

    1. Junwei Hu & Lihong Wang, 2023. "A weighted U-statistic based change point test for multivariate time series," Statistical Papers, Springer, vol. 64(3), pages 753-778, June.
    2. Zdeněk Drábek & Miloš Kopa & Matúš Maciak & Michal Pešta & Sebastiano Vitali, 2023. "Investment disputes and their explicit role in option market uncertainty and overall risk instability," Computational Management Science, Springer, vol. 20(1), pages 1-25, December.
    3. Kai Wenger & Christian Leschinski & Philipp Sibbertsen, 2019. "Change-in-mean tests in long-memory time series: a review of recent developments," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 237-256, June.
    4. Alfredas Račkauskas & Martin Wendler, 2020. "Convergence of U-processes in Hölder spaces with application to robust detection of a changed segment," Statistical Papers, Springer, vol. 61(4), pages 1409-1435, August.
    5. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2018. "A simple test on structural change in long-memory time series," Economics Letters, Elsevier, vol. 163(C), pages 90-94.
    6. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    7. Wingert, Simon & Mboya, Mwasi Paza & Sibbertsen, Philipp, 2020. "Distinguishing between breaks in the mean and breaks in persistence under long memory," Economics Letters, Elsevier, vol. 193(C).
    8. Sibbertsen, Philipp & Wenger, Kai & Wingert, Simon, 2020. "Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series," Hannover Economic Papers (HEP) dp-676, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Wenger, Kai & Leschinski, Christian, 2021. "Fixed-bandwidth CUSUM tests under long memory," Econometrics and Statistics, Elsevier, vol. 20(C), pages 46-61.
    10. Choi, Ji-Eun & Shin, Dong Wan, 2020. "A self-normalization test for correlation change," Economics Letters, Elsevier, vol. 193(C).
    11. Wenger, Kai & Less, Vivien, 2020. "A modified Wilcoxon test for change points in long-range dependent time series," Economics Letters, Elsevier, vol. 192(C).
    12. Daiqing Xi & Tianxiao Pang, 2021. "Estimating multiple breaks in mean sequentially with fractionally integrated errors," Statistical Papers, Springer, vol. 62(1), pages 451-494, February.
    13. Matúš Maciak & Michal Pešta & Barbora Peštová, 2020. "Changepoint in dependent and non-stationary panels," Statistical Papers, Springer, vol. 61(4), pages 1385-1407, August.
    14. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
    15. Zhanshou Chen & Yanting Xiao & Fuxiao Li, 2021. "Monitoring memory parameter change-points in long-memory time series," Empirical Economics, Springer, vol. 60(5), pages 2365-2389, May.
    16. Michal Pešta & Martin Wendler, 2020. "Nuisance-parameter-free changepoint detection in non-stationary series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 379-408, June.
    17. Lazar, Emese & Wang, Shixuan & Xue, Xiaohan, 2023. "Loss function-based change point detection in risk measures," European Journal of Operational Research, Elsevier, vol. 310(1), pages 415-431.

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