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Block wild bootstrap-based CUSUM tests robust to high persistence and misspecification

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  • Lee, Taewook
  • Baek, Changryong

Abstract

It is well-known that the conventional CUSUM tests are over-sized in the presence of high persistence and misspecification. In this article, we propose a block wild bootstrap-based CUSUM test (CUSUM-BWB) for detecting changes in mean and variance shifts under possible high persistence and misspecification. We establish the asymptotic properties of the proposed test and our simulation study shows that CUSUM-BWB tests achieve the correct sizes and comparable powers in finite samples. Our method is also applied to the realized volatility of the KOSPI stock index.

Suggested Citation

  • Lee, Taewook & Baek, Changryong, 2020. "Block wild bootstrap-based CUSUM tests robust to high persistence and misspecification," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:csdana:v:150:y:2020:i:c:s0167947320300876
    DOI: 10.1016/j.csda.2020.106996
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    References listed on IDEAS

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    1. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    2. Taewook Lee & Moosup Kim & Changryong Baek, 2015. "Tests for Volatility Shifts in Garch Against Long-Range Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 127-153, March.
    3. Zhou Zhou, 2013. "Heteroscedasticity and Autocorrelation Robust Structural Change Detection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 726-740, June.
    4. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    5. Alexander Aue & Lajos Horváth, 2013. "Structural breaks in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 1-16, January.
    6. Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.
    7. Juhl, Ted & Xiao, Zhijie, 2009. "Tests for changing mean with monotonic power," Journal of Econometrics, Elsevier, vol. 148(1), pages 14-24, January.
    8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    9. Jean-Yves Pitarakis, 2004. "Least squares estimation and tests of breaks in mean and variance under misspecification," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 32-54, June.
    10. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    11. Changryong Baek & Vladas Pipiras, 2012. "Statistical tests for a single change in mean against long‐range dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 131-151, January.
    12. F. Azizzadeh & S. Rezakhah, 2014. "The CUSUM Test for Detecting Structural Changes in Strong Mixing Processes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(17), pages 3733-3750, September.
    13. Axel Bücher & Jean‐David Fermanian & Ivan Kojadinovic, 2019. "Combining Cumulative Sum Change‐Point Detection Tests for Assessing the Stationarity of Univariate Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(1), pages 124-150, January.
    14. Song, Junmo & Baek, Changryong, 2019. "Detecting structural breaks in realized volatility," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 58-75.
    15. Karl Whelan, 2005. "Testing parameter stability : a wild bootstrap approach," Open Access publications 10197/225, School of Economics, University College Dublin.
    16. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    17. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
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