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- W4224232339 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 (DCCA) method represents the most used one. In this paper, we prove the robustness of the DCCA 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." @default.
- W4224232339 created "2022-04-26" @default.
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- W4224232339 date "2022-04-21" @default.
- W4224232339 modified "2023-09-27" @default.
- W4224232339 title "Robustness of Detrended Cross-correlation Analysis Method Under Outliers Observations" @default.
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- W4224232339 doi "https://doi.org/10.1142/s0219477522500390" @default.
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