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Robustness of Detrended Cross-correlation Analysis Method Under Outliers Observations

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  • Zouhaier Dhifaoui

    (Department of family and community medicine, Faculty of medicine of Sousse, Mohamed Karoui street 4002, Tunisia)

Abstract

The computation of the bivariate Hurst exponent constitutes an important technique to test the power-law cross-correlation of time series. For this objective, the detrended cross-correlation analysis method represents the most used one. In this article, we prove the robustness of the detrended cross-correlation analysis method, where the trend is estimated using the polynomial fitting, to estimate the bivariate Hurst exponent when time series are corrupted by outliers observations. On the other hand, we give the exact polynomial order and a regression region for computing a detrended cross-correlation function to obtain a least-square estimator of bivariate Hurst exponent. Our theoretical results are shown by a simulation study on a two-fractional Gaussian noise process corrupted by outliers observations. Additionally, our results are applied to financial time series. The empirical findings results are accompanied by interpretations.

Suggested Citation

  • Zouhaier Dhifaoui, 2021. "Robustness of Detrended Cross-correlation Analysis Method Under Outliers Observations," Working Papers hal-03411380, HAL.
    • Handle: RePEc:hal:wpaper:hal-03411380
    Note: View the original document on HAL open archive server: https://hal.science/hal-03411380
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    References listed on IDEAS

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