IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v523y2019icp1057-1071.html
   My bibliography  Save this article

Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies

Author

Listed:
  • Kristjanpoller, Werner
  • Bouri, Elie

Abstract

The price behavior of cryptocurrencies relative to conventional currencies remains relatively understudied, despite some attempts that consider the Bitcoin market. This study examines long-range cross-correlations and asymmetric multifractality between leading conventional currencies (Swiss Franc, Euro, British Pound, Yen, and Australian dollar) and main cryptocurrencies (Bitcoin, Litecoin, Ripple, Monero, and Dash) from June 2, 2014 to February 28, 2018. Empirical results show evidence of a significant asymmetric characteristic from the cross-correlation, that is found to be persistent and multifractal in most of the cases. Bitcoin and Litecoin are the cryptocurrencies that exhibit the most multifractal behavior, whereas Monero and Ripple generally exhibit lower multifractal behavior. All cryptocurrencies exhibit a slightly lower asymmetry for longer terms.

Suggested Citation

  • Kristjanpoller, Werner & Bouri, Elie, 2019. "Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1057-1071.
    • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:1057-1071
    DOI: 10.1016/j.physa.2019.04.115
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119304972
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.04.115?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wen-Jie Xie & Zhi-Qiang Jiang & Gao-Feng Gu & Xiong Xiong & Wei-Xing Zhou, 2015. "Joint multifractal analysis based on the partition function approach: Analytical analysis, numerical simulation and empirical application," Papers 1509.05952, arXiv.org.
    2. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    3. Selgin, George, 2015. "Synthetic commodity money," Journal of Financial Stability, Elsevier, vol. 17(C), pages 92-99.
    4. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    5. Alvarez-Ramirez, J. & Rodriguez, E. & Ibarra-Valdez, C., 2018. "Long-range correlations and asymmetry in the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 948-955.
    6. 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.
    7. Zhi-Qiang Jiang & Wen-Jie Xie & Wei-Xing Zhou & Didier Sornette, 2018. "Multifractal analysis of financial markets," Papers 1805.04750, arXiv.org.
    8. 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.
    9. Cao, Guangxi & Xu, Wei, 2016. "Multifractal features of EUA and CER futures markets by using multifractal detrended fluctuation analysis based on empirical model decomposition," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 212-222.
    10. Gvozdanovic, Igor & Podobnik, Boris & Wang, Duan & Eugene Stanley, H., 2012. "1/f behavior in cross-correlations between absolute returns in a US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2860-2866.
    11. 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.
    12. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    13. Gajardo, Gabriel & Kristjanpoller, Werner, 2017. "Asymmetric multifractal cross-correlations and time varying features between Latin-American stock market indices and crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 121-128.
    14. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    15. Ji, Qiang & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2018. "Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 203-213.
    16. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    17. El Alaoui, Marwane & Benbachir, Saâd, 2013. "Multifractal detrended cross-correlation analysis in the MENA area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5985-5993.
    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. Fan, Qingju, 2016. "Asymmetric multiscale detrended fluctuation analysis of California electricity spot price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 252-260.
    20. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
    21. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.
    22. Gajardo, Gabriel & Kristjanpoller, Werner D. & Minutolo, Marcel, 2018. "Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 195-205.
    23. Xi-Yuan Qian & Ya-Min Liu & Zhi-Qiang Jiang & Boris Podobnik & Wei-Xing Zhou & H. Eugene Stanley, 2015. "Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces," Papers 1504.02435, arXiv.org, revised Apr 2015.
    24. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    3. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    4. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    5. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    6. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    7. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    8. Kristjanpoller, Werner & Nekhili, Ramzi & Bouri, Elie, 2024. "Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    9. Pal, Mayukha & Kiran, V. Satya & Rao, P. Madhusudana & Manimaran, P., 2016. "Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 288-293.
    10. Alaoui, Marwane El & Bouri, Elie & Roubaud, David, 2019. "Bitcoin price–volume: A multifractal cross-correlation approach," Finance Research Letters, Elsevier, vol. 31(C).
    11. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.
    12. Ruan, Qingsong & Jiang, Wei & Ma, Guofeng, 2016. "Cross-correlations between price and volume in Chinese gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 10-22.
    13. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    14. Kristjanpoller, Werner & Minutolo, Marcel C., 2021. "Asymmetric multi-fractal cross-correlations of the price of electricity in the US with crude oil and the natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    15. Chen, Yuwen & Zheng, Tingting, 2017. "Asymmetric joint multifractal analysis in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 10-19.
    16. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    17. Ruan, Qingsong & Cui, Hao & Fan, Liming, 2020. "China’s soybean crush spread: Nonlinear analysis based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    18. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    19. Wang, Yiduan & Zheng, Shenzhou & Zhang, Wei & Wang, Guochao & Wang, Jun, 2018. "Fuzzy entropy complexity and multifractal behavior of statistical physics financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 486-498.
    20. Chatterjee, Sucharita, 2020. "Analysis of the human gait rhythm in Neurodegenerative disease: A multifractal approach using Multifractal detrended cross correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:1057-1071. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.