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On the multifractal cross-correlations and coupling coordination characteristics of Fintech, global technology and bitcoin markets

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  • Li, Xing
  • Yu, Hongxia

Abstract

In this study, the multifractal cross-correlations characteristics and coupling coordination between Fintch, global technology, and bitcoin markets are investigated. The empirical results illustrate that the cross-correlations between returns of these markets are multifractal. The multifractal characteristics and multifractal causes analysis illustrated that the apparent and intrinsic multifractal cross-correlations between the return pairs of global technology and bitcoin markets present stronger features. The evolution analysis shows that the volatility of multifractal features between return pairs of Fintech and global technology markets is stronger. Most of the return pairs of these markets are at the level of coordination.

Suggested Citation

  • Li, Xing & Yu, Hongxia, 2025. "On the multifractal cross-correlations and coupling coordination characteristics of Fintech, global technology and bitcoin markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 671(C).
  • Handle: RePEc:eee:phsmap:v:671:y:2025:i:c:s0378437125002973
    DOI: 10.1016/j.physa.2025.130645
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    1. Assaf, Ata & Demir, Ender & Mokni, Khaled, 2024. "Exploring connectedness among cryptocurrency, technology communication, and FinTech through dynamic and fractal analysis," Finance Research Letters, Elsevier, vol. 63(C).
    2. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2022. "Commodity and financial markets’ fear before and during COVID-19 pandemic: Persistence and causality analyses," Resources Policy, Elsevier, vol. 76(C).
    3. Fung, Derrick W.H. & Lee, Wing Yan & Yeh, Jason J.H. & Yuen, Fei Lung, 2020. "Friend or foe: The divergent effects of FinTech on financial stability," Emerging Markets Review, Elsevier, vol. 45(C).
    4. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A. & Tabak, Benjamin M., 2023. "Multifractal cross-correlations between green bonds and financial assets," Finance Research Letters, Elsevier, vol. 53(C).
    5. Tao Zhou & Rui Ding & Yiming Du & Yilin Zhang & Shihui Cheng & Ting Zhang, 2022. "Study on the Coupling Coordination and Spatial Correlation Effect of Green Finance and High-Quality Economic Development—Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    6. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    7. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    8. Rak, Rafał & Grech, Dariusz, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 48-66.
    9. Daud, Siti Nurazira Mohd & Ahmad, Abd Halim & Khalid, Airil & Azman-Saini, W.N.W., 2022. "FinTech and financial stability: Threat or opportunity?," Finance Research Letters, Elsevier, vol. 47(PB).
    10. Li, Xing, 2021. "On the multifractal analysis of air quality index time series before and during COVID-19 partial lockdown: A case study of Shanghai, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    11. Omarova, Saule T. & Library, Cornell, 2018. "New Tech v. New Deal: Fintech as a Systemic Phenomenon," LawRxiv 9v3p2, Center for Open Science.
    12. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    13. Petre Caraiani, 2012. "Evidence of Multifractality from Emerging European Stock Markets," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    14. Zhang, Xin & Yang, Liansheng & Zhu, Yingming, 2019. "Analysis of multifractal characterization of Bitcoin market based on multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 973-983.
    15. Chen, Feier & Miao, Yuqi & Tian, Kang & Ding, Xiaoxu & Li, Tingyi, 2017. "Multifractal cross-correlations between crude oil and tanker freight rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 344-354.
    16. He, Ling-Yun & Chen, Shu-Peng, 2011. "Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets," Chaos, Solitons & Fractals, Elsevier, vol. 44(6), pages 355-361.
    17. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    18. Cao, Guangxi & Xu, Longbing & Cao, Jie, 2012. "Multifractal detrended cross-correlations between the Chinese exchange market and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4855-4866.
    19. Kwapień, J. & Oświe¸cimka, P. & Drożdż, S., 2005. "Components of multifractality in high-frequency stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 466-474.
    20. Zhou, Wei-Xing, 2012. "Finite-size effect and the components of multifractality in financial volatility," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 147-155.
    21. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    22. Ma, Feng & Wei, Yu & Huang, Dengshi, 2013. "Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1659-1670.
    23. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    24. Omarova, Saule T., 2018. "New Tech v. New Deal: Fintech as a Systemic Phenomenon," LawArchive 9v3p2_v1, Center for Open Science.
    25. Dai, Meifeng & Hou, Jie & Gao, Jianyu & Su, Weiyi & Xi, Lifeng & Ye, Dandan, 2016. "Mixed multifractal analysis of China and US stock index series," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 268-275.
    26. Rafal Rak & Dariusz Grech, 2018. "Quantitative approach to multifractality induced by correlations and broad distribution of data," Papers 1805.11909, arXiv.org.
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