IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v68y2023ics106294082300092x.html
   My bibliography  Save this article

Liquidity spillovers between cryptocurrency and foreign exchange markets

Author

Listed:
  • Nekhili, Ramzi
  • Sultan, Jahangir
  • Bouri, Elie

Abstract

Market liquidity spillover has been studied using fiat and digital currency (cryptocurrency), though separately. In today’s globally connected financial markets, there is interconnectedness among financial assets, as economic agents make decisions involving multiple asset classes. In this paper, we construct daily liquidity measures for five major cryptocurrencies and seven major fiat currencies and examine their interdependence in the time–frequency domain. We find that liquidity connectedness is event-driven and varies with time. Notably, there is an increase in liquidity spillover at the peak of the COVID-19 pandemic, reflecting heightened uncertainty and market instability. We also find that, at the peak of the pandemic, the total spillover index is stronger in the long run than the short run, highlighting a possible flight-to-liquidity during periods of stress. The Euro stands out as the principal net transmitter of liquidity shocks in the short run, while Ethereum plays this role in the long run. Further analysis highlights the role of some economic and financial variables in driving the dynamics of liquidity spillovers and reveals some heterogeneity in the identity of drivers between the short and long run. The results enrich the academic literature by providing evidence of liquidity spillovers between cryptocurrencies and foreign exchange markets during times of stress, which is insightful for traders, investors, and policymakers.

Suggested Citation

  • Nekhili, Ramzi & Sultan, Jahangir & Bouri, Elie, 2023. "Liquidity spillovers between cryptocurrency and foreign exchange markets," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:ecofin:v:68:y:2023:i:c:s106294082300092x
    DOI: 10.1016/j.najef.2023.101969
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106294082300092X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2023.101969?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. Oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2007. "Market efficiency in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 209-212.
    2. 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.
    3. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2022. "Liquidity spillover in foreign exchange markets," Finance Research Letters, Elsevier, vol. 44(C).
    4. Shu-Han Hsu, 2022. "Investigating the Co-Volatility Spillover Effects between Cryptocurrencies and Currencies at Different Natures of Risk Events," JRFM, MDPI, vol. 15(9), pages 1-15, August.
    5. Brauneis, Alexander & Mestel, Roland & Theissen, Erik, 2021. "What drives the liquidity of cryptocurrencies? A long-term analysis," Finance Research Letters, Elsevier, vol. 39(C).
    6. Baumöhl, Eduard, 2019. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," Finance Research Letters, Elsevier, vol. 29(C), pages 363-372.
    7. Sensoy, Ahmet & Uzun, Sevcan & Lucey, Brian M., 2021. "Commonality in FX liquidity: High-frequency evidence," Finance Research Letters, Elsevier, vol. 39(C).
    8. 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.
    9. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Larkin, Charles & Lucey, Brian & Oxley, Les, 2022. "Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    10. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    11. Rösch, Christoph G. & Kaserer, Christoph, 2014. "Reprint of: Market liquidity in the financial crisis: The role of liquidity commonality and flight-to-quality," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 152-170.
    12. Mensi, Walid & El Khoury, Rim & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Yue, Wei & Zhang, Sijia & Zhang, Qiang, 2021. "Asymmetric News Effects on Cryptocurrency Liquidity: an Event Study Perspective," Finance Research Letters, Elsevier, vol. 41(C).
    14. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2022. "Bitcoin unchained: Determinants of cryptocurrency exchange liquidity," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 106-122.
    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. Wan, Jieru & Yin, Libo & Wu, You, 2024. "Return and volatility connectedness across global ESG stock indexes: Evidence from the time-frequency domain analysis," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 397-428.
    2. Joo, Young C. & Park, Sung Y., 2024. "Hedging Bitcoin with commodity futures: An analysis with copper, gas, gold, and crude oil futures," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    3. Kostas Giannopoulos & Ramzi Nekhili & Christos Christodoulou-Volos, 2024. "Estimating Tail Risk in Ultra-High-Frequency Cryptocurrency Data," IJFS, MDPI, vol. 12(4), pages 1-14, October.
    4. Zhou, Donghai & Liu, Xiaoxing & Tang, Chun, 2024. "Does the international oil market interact with China’s financial market? New evidence from time-varying higher moments," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    5. Narayan, Shivani & Kumar, Dilip, 2024. "Unveiling interconnectedness and risk spillover among cryptocurrencies and other asset classes," Global Finance Journal, Elsevier, vol. 62(C).
    6. Yousaf, Imran & Assaf, Ata & Demir, Ender, 2024. "Relationship between real estate tokens and other asset classes: Evidence from quantile connectedness approach," Research in International Business and Finance, Elsevier, vol. 69(C).
    7. Abakah, Emmanuel Joel Aikins & Wali Ullah, G M & Abdullah, Mohammad & Lee, Chi-Chuan & Sulong, Zunaidah, 2024. "Correlation structure between fiat currencies and blockchain assets," Finance Research Letters, Elsevier, vol. 62(PA).

    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. Gök, Remzi & Bouri, Elie & Gemici, Eray, 2023. "Volatility spillovers between sovereign CDS and futures markets in various volatility states: Evidence from an emerging economy around the pandemic," Research in International Business and Finance, Elsevier, vol. 66(C).
    2. Raza, Syed Ali & Shah, Nida & Guesmi, Khaled & Msolli, Badreddine, 2022. "How does COVID-19 influence dynamic spillover connectedness between cryptocurrencies? Evidence from non-parametric causality-in-quantiles techniques," Finance Research Letters, Elsevier, vol. 47(PA).
    3. Asil Azimli, 2024. "Time-varying spillovers in high-order moments among cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-39, December.
    4. Muhammad Anas & Syed Jawad Hussain Shahzad & Larisa Yarovaya, 2024. "The use of high-frequency data in cryptocurrency research: a meta-review of literature with bibliometric analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
    5. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2023. "Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 64(C).
    6. Abrar, Afsheen & Naeem, Muhammad Abubakr & Karim, Sitara & Lucey, Brian M. & Vigne, Samuel A., 2024. "Shining in or fading out: Do precious metals sparkle for cryptocurrencies?," Resources Policy, Elsevier, vol. 90(C).
    7. Suardi, Sandy & Xu, Caihong & Zhou, Z. Ivy, 2022. "COVID-19 pandemic and liquidity commonality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    8. Erdinc Akyildirim & Ahmet Faruk Aysan & Oguzhan Cepni & Özge Serbest, 2024. "Sentiment matters: the effect of news-media on spillovers among cryptocurrency returns," The European Journal of Finance, Taylor & Francis Journals, vol. 30(14), pages 1577-1613, September.
    9. Liew, Ping-Xin & Lim, Kian-Ping & Goh, Kim-Leng, 2022. "The dynamics and determinants of liquidity connectedness across financial asset markets," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 341-358.
    10. Lee, Min-Jae & Choi, Sun-Yong, 2024. "Insights into the dynamics of market efficiency spillover of financial assets in different equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    11. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    12. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    13. Aysan, Ahmet Faruk & Batten, Jonathan & Gozgor, Giray & Khalfaoui, Rabeh & Nanaeva, Zhamal, 2024. "Metaverse and financial markets: A quantile-time-frequency connectedness analysis," Research in International Business and Finance, Elsevier, vol. 72(PB).
    14. Youtao Xiang & Sumuya Borjigin, 2024. "High–low volatility spillover network between economic policy uncertainty and commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1295-1319, August.
    15. Elsayed, Ahmed H. & Asutay, Mehmet & ElAlaoui, Abdelkader O. & Bin Jusoh, Hashim, 2024. "Volatility spillover across spot and futures markets: Evidence from dual financial system," Research in International Business and Finance, Elsevier, vol. 71(C).
    16. Gabauer, David & Chatziantoniou, Ioannis & Stenfors, Alexis, 2023. "Model-free connectedness measures," Finance Research Letters, Elsevier, vol. 54(C).
    17. Duan, Kun & Zhao, Yanqi & Urquhart, Andrew & Huang, Yingying, 2023. "Do clean and dirty cryptocurrencies connect with financial assets differently? The role of economic policy uncertainty," Energy Economics, Elsevier, vol. 127(PA).
    18. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    19. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    20. Ji, Hao & Naeem, Muhammad & Zhang, Jing & Tiwari, Aviral Kumar, 2024. "Dynamic dependence and spillover among the energy related ETFs: From the hedging effectiveness perspective," Energy Economics, Elsevier, vol. 136(C).

    More about this item

    Keywords

    Liquidity measure; Time and frequency spillovers; Bitcoin; Cryptocurrency; Fiat currencies; COVID-19 outbreak;
    All these keywords.

    JEL classification:

    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

    Statistics

    Access and download statistics

    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:ecofin:v:68:y:2023:i:c:s106294082300092x. 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.elsevier.com/locate/inca/620163 .

    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.