IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v581y2021ics0378437121005100.html
   My bibliography  Save this article

Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets

Author

Listed:
  • Kakinaka, Shinji
  • Umeno, Ken

Abstract

Asymmetric relationship between price and volatility is a prominent feature of the financial market time series. This paper explores the price–volatility nexus in cryptocurrency markets and investigates the presence of asymmetric volatility effect between uptrend (bull) and downtrend (bear) regimes. The conventional GARCH-class models have shown that in cryptocurrency markets, asymmetric reactions of volatility to returns differ from those of other traditional financial assets. We address this issue from a viewpoint of fractal analysis, which can cover the nonlinear interactions and the self-similarity properties widely acknowledged in the field of econophysics. The asymmetric cross-correlations between price and volatility for Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC) during the period from June 1, 2016 to December 28, 2020 are investigated using the MF-ADCCA method and quantified via the asymmetric DCCA coefficient. The approaches take into account the nonlinearity and asymmetric multifractal scaling properties, providing new insights in investigating the relationships in a dynamical way. We find that cross-correlations are stronger in downtrend markets than in uptrend markets for maturing BTC and ETH. In contrast, for XRP and LTC, inverted reactions are present where cross-correlations are stronger in uptrend markets.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:581:y:2021:i:c:s0378437121005100
    DOI: 10.1016/j.physa.2021.126237
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121005100
    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.2021.126237?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. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    2. 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.
    3. Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar & H. Eugene Stanley & Boris Podobnik, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Papers 1803.08405, arXiv.org.
    4. Rebecca J. Sela & Clifford M. Hurvich, 2012. "The averaged periodogram estimator for a power law in coherency," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(2), pages 340-363, March.
    5. Wei Zhang & Pengfei Wang & Xiao Li & Dehua Shen, 2018. "Multifractal Detrended Cross-Correlation Analysis of the Return-Volume Relationship of Bitcoin Market," Complexity, Hindawi, vol. 2018, pages 1-20, July.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    7. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    8. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    9. Guangxi Cao & Ling-Yun He & Jie Cao, 2018. "Multifractal Detrended Analysis Method and Its Application in Financial Markets," Springer Books, Springer, number 978-981-10-7916-0, January.
    10. Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
    11. Stavroyiannis, Stavros & Babalos, Vassilios & Bekiros, Stelios & Lahmiri, Salim & Uddin, Gazi Salah, 2019. "The high frequency multifractal properties of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 62-71.
    12. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    13. 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.
    14. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "The Impact of Trades on Daily Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1241-1277.
    15. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    16. Tiwari, Aviral Kumar & Jana, R.K. & Das, Debojyoti & Roubaud, David, 2018. "Informational efficiency of Bitcoin—An extension," Economics Letters, Elsevier, vol. 163(C), pages 106-109.
    17. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    18. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Carlos Echeverria, Juan, 2009. "A DFA approach for assessing asymmetric correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2263-2270.
    19. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    20. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    21. He, Ling-Yun & Chen, Shu-Peng, 2011. "A new approach to quantify power-law cross-correlation and its application to commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3806-3814.
    22. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    23. Begušić, Stjepan & Kostanjčar, Zvonko & Eugene Stanley, H. & Podobnik, Boris, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 400-406.
    24. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
    25. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    26. White, Reilly & Marinakis, Yorgos & Islam, Nazrul & Walsh, Steven, 2020. "Is Bitcoin a currency, a technology-based product, or something else?," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    27. 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.
    28. 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.
    29. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    30. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    31. Stanis{l}aw Dro.zd.z & Robert Gk{e}barowski & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marcin Wk{a}torek, 2018. "Bitcoin market route to maturity? Evidence from return fluctuations, temporal correlations and multiscaling effects," Papers 1804.05916, arXiv.org, revised Jul 2018.
    32. 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.
    33. repec:arx:papers:1501.02947 is not listed on IDEAS
    34. Lee, Minhyuk & Song, Jae Wook & Park, Ji Hwan & Chang, Woojin, 2017. "Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA," Chaos, Solitons & Fractals, Elsevier, vol. 97(C), pages 28-38.
    35. Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    36. Pawe{l} O'swic{e}cimka & Stanis{l}aw Dro.zd.z & Marcin Forczek & Stanis{l}aw Jadach & Jaros{l}aw Kwapie'n, 2013. "Detrended Cross-Correlation Analysis Consistently Extended to Multifractality," Papers 1308.6148, arXiv.org, revised Feb 2014.
    37. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    38. 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.
    39. Wang, Yudong & Liu, Li & Gu, Rongbao, 2009. "Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 271-276, December.
    40. Blau, Benjamin M., 2018. "Price dynamics and speculative trading in Bitcoin," Research in International Business and Finance, Elsevier, vol. 43(C), pages 15-21.
    41. da Silva Filho, Antônio Carlos & Maganini, Natália Diniz & de Almeida, Eduardo Fonseca, 2018. "Multifractal analysis of Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 954-967.
    42. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    43. 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.
    44. Baur, Dirk G. & Dimpfl, Thomas, 2018. "Asymmetric volatility in cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 148-151.
    45. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    46. Thompson, James R. & Wilson, James R., 2016. "Multifractal detrended fluctuation analysis: Practical applications to financial time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 126(C), pages 63-88.
    47. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    48. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
    2. Kakinaka, Shinji & Umeno, Ken, 2022. "Asymmetric volatility dynamics in cryptocurrency markets on multi-time scales," Research in International Business and Finance, Elsevier, vol. 62(C).
    3. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Alam, Masud & Abedin, Mohammad Zoynul & Shi, Baofeng, 2023. "NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    5. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    6. Abdullah, Mohammad & Chowdhury, Mohammad Ashraful Ferdous & Sulong, Zunaidah, 2023. "Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications," Resources Policy, Elsevier, vol. 81(C).

    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. Kakinaka, Shinji & Umeno, Ken, 2022. "Asymmetric volatility dynamics in cryptocurrency markets on multi-time scales," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. 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).
    3. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    4. 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.
    5. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    6. Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
    7. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    8. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    9. 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.
    10. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Alam, Masud & Abedin, Mohammad Zoynul & Shi, Baofeng, 2023. "NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    11. Telli, Şahin & Chen, Hongzhuan, 2021. "Multifractal behavior relationship between crypto markets and Wikipedia-Reddit online platforms," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    12. Stefano Martinazzi & Daniele Regoli & Andrea Flori, 2020. "A Tale of Two Layers: The Mutual Relationship between Bitcoin and Lightning Network," Risks, MDPI, vol. 8(4), pages 1-18, December.
    13. Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
    14. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    15. Tetsuya Takaishi & Takanori Adachi, 2020. "Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 145-154, March.
    16. Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.
    17. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    18. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    19. T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
    20. Li, Mu-Yao & Cai, Qing & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Exponentially decayed double power-law distribution of Bitcoin trade sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(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:581:y:2021:i:c:s0378437121005100. 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.