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Measuring nonlinear dependence in time‐series, a distance correlation approach

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  • Zhou Zhou

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  • Zhou Zhou, 2012. "Measuring nonlinear dependence in time‐series, a distance correlation approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(3), pages 438-457, May.
    • Handle: RePEc:bla:jtsera:v:33:y:2012:i:3:p:438-457
    DOI: j.1467-9892.2011.00780.x
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    Cited by:

    1. Bampinas, Georgios & Panagiotidis, Theodore, 2024. "How would the war and the pandemic affect the stock and cryptocurrency cross-market linkages?," Research in International Business and Finance, Elsevier, vol. 70(PA).
    2. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    3. Chaudhuri, Arin & Hu, Wenhao, 2019. "A fast algorithm for computing distance correlation," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 15-24.
    4. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2017. "A diagram to detect serial dependencies: an application to transport time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 581-594, March.
    5. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Detecting serial dependencies with the reproducibility probability autodependogram," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 35-61, January.
    6. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    7. Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis N., 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Journal of International Money and Finance, Elsevier, vol. 137(C).
    8. L. Bagnato & L. De Capitani & A. Punzo, 2016. "The Kullback–Leibler autodependogram," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2574-2594, October.
    9. Jentsch, Carsten & Leucht, Anne & Meyer, Marco & Beering, Carina, 2016. "Empirical characteristic functions-based estimation and distance correlation for locally stationary processes," Working Papers 16-15, University of Mannheim, Department of Economics.
    10. Matsui, Muneya & Mikosch, Thomas & Roozegar, Rasool & Tafakori, Laleh, 2022. "Distance covariance for random fields," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 280-322.
    11. Wan, Phyllis & Davis, Richard A., 2022. "Goodness-of-fit testing for time series models via distance covariance," Journal of Econometrics, Elsevier, vol. 227(1), pages 4-24.
    12. Tata Subba Rao & Granville Tunnicliffe Wilson & Geir Drage Berentsen & Ricardo Cao & Mario Francisco-Fernández & Dag TjØstheim, 2017. "Some Properties of Local Gaussian Correlation and Other Nonlinear Dependence Measures," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 352-380, March.
    13. Shang, Du & Shang, Pengjian, 2022. "The dependence measurements based on martingale difference correlation and distance correlation: Efficient tools to distinguish different complex systems," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    14. Hui, Yongchang & Wong, Wing-Keung & Bai, Zhidong & Zhu, Zhenzhen, 2016. "A New Nonlinearity Test to Circumvent the Limitation of Volterra Expansion with Applications," MPRA Paper 75216, University Library of Munich, Germany.
    15. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2018. "Testing for Serial Independence: Beyond the Portmanteau Approach," The American Statistician, Taylor & Francis Journals, vol. 72(3), pages 219-238, July.
    16. Chu, Ba, 2023. "A distance-based test of independence between two multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    17. Dueck, Johannes & Edelmann, Dominic & Richards, Donald, 2015. "A generalization of an integral arising in the theory of distance correlation," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 116-119.
    18. Dueck, Johannes & Edelmann, Dominic & Richards, Donald, 2017. "Distance correlation coefficients for Lancaster distributions," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 19-39.
    19. Cui, Yan & Yang, Jun & Zhou, Zhou, 2023. "State-domain change point detection for nonlinear time series regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 3-27.
    20. Dominic Edelmann & Tobias Terzer & Donald Richards, 2021. "A Basic Treatment of the Distance Covariance," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 12-25, May.
    21. Cencheng Shen & Joshua T. Vogelstein, 2021. "The exact equivalence of distance and kernel methods in hypothesis testing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 385-403, September.
    22. Virginia Lacal & Dag TjØstheim, 2017. "Local Gaussian Autocorrelation and Tests for Serial Independence," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 51-71, January.

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