Multifractal Detrended Partial Cross-Correlation and Risk Transmission of Cryptocurrencies

By taking Bitcoin, Ethereum, and Ripple as research objects, this paper applies the multifractal detrended partial cross-correlation analysis (MF-DPXA) to study the intrinsic cross-correlation between cryptocurrencies. Combining MF-DPXA and time-delay DCCA methods, we develop the removing factors time-delayed detrended cross-correlation analysis (R-TD-DCCA) to study the risk transmission direction between cryptocurrencies after removing the influence of common factors. The results show that after removing the influence of cryptocurrencies, the persistence of the cross-correlation between cryptocurrencies is enhanced, and the multifractal degrees of the cross-correlation between Bitcoin and Ethereum and between Ethereum and Ripple are increased, but the multifractal degree of the cross-correlation between Bitcoin and Ripple is weakened. However, after removing the influence of the S&P 500 index, the multifractal degree of the cross-correlation between cryptocurrencies has weakened. The Hurst exponent of local dynamic cross-correlation between cryptocurrencies is almost always greater than 0.5. With the increase in time delay, the risk of Bitcoin is mainly transmitted to Ethereum and Ripple, and the risk of Ripple is mainly transmitted to Ethereum. When removing the impact of the S&P 500 index, the short-term risk of Bitcoin is mainly transmitted to Ethereum and Ripple. The findings of this study have several implications for re-understanding the intrinsic interdependence structure and portfolios.

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Publication Details

Journal
Fluctuation and Noise Letters
Published
2024-12-20
DOI
https://doi.org/10.1142/s0219477525500269
Citations
1
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
1.13
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article

Multifractal Detrended Partial Cross-Correlation and Risk Transmission of Cryptocurrencies

Wenhao Xie, Guangxi Cao
1 citations
Fluctuation and Noise Letters
Complex Systems and Time Series Analysis
1.13
article

Multifractal Detrended Partial Cross-Correlation and Risk Transmission of Cryptocurrencies

Wenhao Xie, Guangxi Cao
article en
1 citations

Abstract

By taking Bitcoin, Ethereum, and Ripple as research objects, this paper applies the multifractal detrended partial cross-correlation analysis (MF-DPXA) to study the intrinsic cross-correlation between cryptocurrencies. Combining MF-DPXA and time-delay DCCA methods, we develop the removing factors time-delayed detrended cross-correlation analysis (R-TD-DCCA) to study the risk transmission direction between cryptocurrencies after removing the influence of common factors. The results show that after removing the influence of cryptocurrencies, the persistence of the cross-correlation between cryptocurrencies is enhanced, and the multifractal degrees of the cross-correlation between Bitcoin and Ethereum and between Ethereum and Ripple are increased, but the multifractal degree of the cross-correlation between Bitcoin and Ripple is weakened. However, after removing the influence of the S&P 500 index, the multifractal degree of the cross-correlation between cryptocurrencies has weakened. The Hurst exponent of local dynamic cross-correlation between cryptocurrencies is almost always greater than 0.5. With the increase in time delay, the risk of Bitcoin is mainly transmitted to Ethereum and Ripple, and the risk of Ripple is mainly transmitted to Ethereum. When removing the impact of the S&P 500 index, the short-term risk of Bitcoin is mainly transmitted to Ethereum and Ripple. The findings of this study have several implications for re-understanding the intrinsic interdependence structure and portfolios.

Fluctuation and Noise LettersVol. 24(03)
Nanjing University of Information Science and Technology (CN), Nanjing University of Science and Technology (CN), Henan University of Urban Construction (CN), Wuxi Institute of Technology (CN)
Zero hunger
Openalex Percentile: Top 10%
Complex Systems and Time Series Analysis
1.13
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