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Liquidity connectedness in cryptocurrency market

Author

Listed:
  • Mudassar Hasan

    (The University of Lahore)

  • Muhammad Abubakr Naeem

    (University College Dublin
    University of Economics Ho Chi Minh City)

  • Muhammad Arif

    (Shaheed Benazir Bhutto University)

  • Syed Jawad Hussain Shahzad

    (Montpellier Business School
    South Ural State University)

  • Xuan Vinh Vo

    (University of Economics Ho Chi Minh City)

Abstract

We examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness.

Suggested Citation

  • Mudassar Hasan & Muhammad Abubakr Naeem & Muhammad Arif & Syed Jawad Hussain Shahzad & Xuan Vinh Vo, 2022. "Liquidity connectedness in cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    • Handle: RePEc:spr:fininn:v:8:y:2022:i:1:d:10.1186_s40854-021-00308-3
    DOI: 10.1186/s40854-021-00308-3
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    as
    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1043-1078, November.
    2. da Gama Silva, Paulo Vitor Jordão & Klotzle, Marcelo Cabus & Pinto, Antonio Carlos Figueiredo & Gomes, Leonardo Lima, 2019. "Herding behavior and contagion in the cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 41-50.
    3. Inekwe, John Nkwoma, 2020. "Liquidity connectedness and output synchronisation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 66(C).
    4. Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
    5. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    6. Faruk Balli & Anne de Bruin & Md Iftekhar Hasan Chowdhury & Muhammad Abubakr Naeem, 2020. "Connectedness of cryptocurrencies and prevailing uncertainties," Applied Economics Letters, Taylor & Francis Journals, vol. 27(16), pages 1316-1322, September.
    7. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    8. Feng Ma & Yaojie Zhang & M. I. M. Wahab & Xiaodong Lai, 2019. "The role of jumps in the agricultural futures market on forecasting stock market volatility: New evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(5), pages 400-414, August.
    9. Bodart, Vincent & Candelon, Bertrand, 2009. "Evidence of interdependence and contagion using a frequency domain framework," Emerging Markets Review, Elsevier, vol. 10(2), pages 140-150, June.
    10. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    11. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "Liquidity commonality in commodities," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 11-20.
    12. Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin J., 2018. "Financial connectedness of BRICS and global sovereign bond markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 1-16.
    13. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    14. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    15. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    16. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
    17. Bouri, Elie & Hussain Shahzad, Syed Jawad & Roubaud, David, 2020. "Cryptocurrencies as hedges and safe-havens for US equity sectors," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 294-307.
    18. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    19. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2021. "Cyber-attacks, spillovers and contagion in the cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    20. Andrew Koch & Stefan Ruenzi & Laura Starks, 2016. "Editor's Choice Commonality in Liquidity: A Demand-Side Explanation," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 1943-1974.
    21. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2012. "Commodity Liquidity Measurement and Transaction Costs," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 599-638.
    22. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    23. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    24. Zięba, Damian & Kokoszczyński, Ryszard & Śledziewska, Katarzyna, 2019. "Shock transmission in the cryptocurrency market. Is Bitcoin the most influential?," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 102-125.
    25. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    26. Baur, Dirk G. & Cahill, Daniel & Godfrey, Keith & (Frank) Liu, Zhangxin, 2019. "Bitcoin time-of-day, day-of-week and month-of-year effects in returns and trading volume," Finance Research Letters, Elsevier, vol. 31(C), pages 78-92.
    27. Allaudeen Hameed & Wenjin Kang & S. Viswanathan, 2010. "Stock Market Declines and Liquidity," Journal of Finance, American Finance Association, vol. 65(1), pages 257-293, February.
    28. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    29. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    30. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    31. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
    32. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    33. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    34. Kamara, Avraham & Lou, Xiaoxia & Sadka, Ronnie, 2008. "The divergence of liquidity commonality in the cross-section of stocks," Journal of Financial Economics, Elsevier, vol. 89(3), pages 444-466, September.
    35. Charlotte Christiansen, 2007. "Volatility‐Spillover Effects in European Bond Markets," European Financial Management, European Financial Management Association, vol. 13(5), pages 923-948, November.
    36. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    37. Syed Jawad Hussain Shahzad & Elie Bouri & Jose Arreola-Hernandez & David Roubaud & Stelios Bekiros, 2019. "Spillover across Eurozone credit market sectors and determinants," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6333-6349, December.
    38. Sean Foley & Jonathan R Karlsen & Tālis J Putniņš, 2019. "Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed through Cryptocurrencies?," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1798-1853.
    39. Smales, L.A., 2019. "Bitcoin as a safe haven: Is it even worth considering?," Finance Research Letters, Elsevier, vol. 30(C), pages 385-393.
    40. Gang Kou & Özlem Olgu Akdeniz & Hasan Dinçer & Serhat Yüksel, 2021. "Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-28, December.
    41. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    42. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    43. Hasbrouck, Joel & Seppi, Duane J., 2001. "Common factors in prices, order flows, and liquidity," Journal of Financial Economics, Elsevier, vol. 59(3), pages 383-411, March.
    44. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Ko, Hee-Un & Yoon, Seong-Min & Kang, Sang Hoon, 2020. "Why cryptocurrency markets are inefficient: The impact of liquidity and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    45. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2019. "Multiresolution analysis and spillovers of major cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 49(C), pages 191-206.
    46. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    47. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr & Vo, Xuan Vinh, 2021. "The pricing of bad contagion in cryptocurrencies: A four-factor pricing model," Finance Research Letters, Elsevier, vol. 41(C).
    48. Scharnowski, Stefan, 2021. "Understanding Bitcoin liquidity," Finance Research Letters, Elsevier, vol. 38(C).
    49. Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    50. Gurdgiev, Constantin & O’Loughlin, Daniel, 2020. "Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    51. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1043-1078, November.
    52. Huynh, Toan Luu Duc & Nasir, Muhammad Ali & Vo, Xuan Vinh & Nguyen, Thong Trung, 2020. "“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    53. Albert S. Hu & Christine A. Parlour & Uday Rajan, 2019. "Cryptocurrencies: Stylized facts on a new investible instrument," Financial Management, Financial Management Association International, vol. 48(4), pages 1049-1068, December.
    54. Kim, Thomas, 2017. "On the transaction cost of Bitcoin," Finance Research Letters, Elsevier, vol. 23(C), pages 300-305.
    55. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    56. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    57. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    58. Hio Loi, 2018. "The Liquidity of Bitcoin," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(1), pages 13-22, January.
    59. Bredin, Don & Conlon, Thomas & Potì, Valerio, 2017. "The price of shelter - Downside risk reduction with precious metals," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 48-58.
    60. Adrian (Wai-Kong) Cheung & Eduardo Roca & Jen-Je Su, 2015. "Crypto-currency bubbles: an application of the Phillips-Shi-Yu (2013) methodology on Mt. Gox bitcoin prices," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2348-2358, May.
    61. Balli, Faruk & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2019. "Spillover network of commodity uncertainties," Energy Economics, Elsevier, vol. 81(C), pages 914-927.
    62. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    63. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    64. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    65. Koutmos, Dimitrios, 2018. "Liquidity uncertainty and Bitcoin’s market microstructure," Economics Letters, Elsevier, vol. 172(C), pages 97-101.
    66. Vidal-Tomás, David & Ibáñez, Ana M. & Farinós, José E., 2019. "Herding in the cryptocurrency market: CSSD and CSAD approaches," Finance Research Letters, Elsevier, vol. 30(C), pages 181-186.
    67. Coughenour, Jay F. & Saad, Mohsen M., 2004. "Common market makers and commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 73(1), pages 37-69, July.
    68. Dyhrberg, Anne H. & Foley, Sean & Svec, Jiri, 2018. "How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets," Economics Letters, Elsevier, vol. 171(C), pages 140-143.
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    More about this item

    Keywords

    Liquidity; Time–frequency connectedness; Cryptocurrencies;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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