IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v44y2022ics1544612321001124.html
   My bibliography  Save this article

Cryptocurrency returns and the volatility of liquidity

Author

Listed:
  • Leirvik, Thomas

Abstract

In this paper I document a positive relation between the volatility of liquidity and expected returns. Specifically, I analyze the relationship between the idiosyncratic volatility of market liquidity and the returns of the five largest cryptocurrencies by market capitalization. I find that the correlation between liquidity volatility and returns is overall significantly positive, but highly time-varying. This implies that investors demand a premium for a high variation in liquidity volatility. I furthermore find that the correlation between returns and the level of liquidity is mostly positive, thus, when liquidity is low, expected returns are high. The results corroborates results from other financial markets.

Suggested Citation

  • Leirvik, Thomas, 2022. "Cryptocurrency returns and the volatility of liquidity," Finance Research Letters, Elsevier, vol. 44(C).
  • Handle: RePEc:eee:finlet:v:44:y:2022:i:c:s1544612321001124
    DOI: 10.1016/j.frl.2021.102031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612321001124
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2021.102031?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. 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).
    2. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    3. Omane-Adjepong, Maurice & Alagidede, Paul & Akosah, Nana Kwame, 2019. "Wavelet time-scale persistence analysis of cryptocurrency market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 105-120.
    4. 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.
    5. Pereira, João Pedro & Zhang, Harold H., 2010. "Stock Returns and the Volatility of Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 1077-1110, August.
    6. Brauneis, Alexander & Mestel, Roland, 2019. "Cryptocurrency-portfolios in a mean-variance framework," Finance Research Letters, Elsevier, vol. 28(C), pages 259-264.
    7. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    8. 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.
    9. Leirvik, Thomas & Fiskerstrand, Sondre R. & Fjellvikås, Anders B., 2017. "Market liquidity and stock returns in the Norwegian stock market," Finance Research Letters, Elsevier, vol. 21(C), pages 272-276.
    10. Andrew Koch & Stefan Ruenzi & Laura Starks, 2016. "Editor's Choice Commonality in Liquidity: A Demand-Side Explanation," Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 1943-1974.
    11. Kristoufek, Ladislav & Vosvrda, Miloslav, 2019. "Cryptocurrencies market efficiency ranking: Not so straightforward," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    12. 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.
    13. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
    14. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    15. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    16. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    17. 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.
    18. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    19. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    20. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2021. "How to measure the liquidity of cryptocurrency markets?," Journal of Banking & Finance, Elsevier, vol. 124(C).
    21. Chu, Jeffrey & Zhang, Yuanyuan & Chan, Stephen, 2019. "The adaptive market hypothesis in the high frequency cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 221-231.
    22. Vidal-Tomás, David & Ibañez, Ana, 2018. "Semi-strong efficiency of Bitcoin," Finance Research Letters, Elsevier, vol. 27(C), pages 259-265.
    23. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    24. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    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. Lars Hornuf & Paul P. Momtaz & Rachel J. Nam & Ye Yuan, 2023. "Cybercrime on the Ethereum Blockchain," CESifo Working Paper Series 10598, CESifo.
    2. Foroutan, Parisa & Lahmiri, Salim, 2022. "The effect of COVID-19 pandemic on return-volume and return-volatility relationships in cryptocurrency markets," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    3. Lee, Chi-Chuan & Yu, Chin-Hsien & Zhang, Jian, 2023. "Heterogeneous dependence among cryptocurrency, green bonds, and sustainable equity: New insights from Granger-causality in quantiles analysis," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 99-109.
    4. 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.
    5. Khalfaoui, Rabeh & Hammoudeh, Shawkat & Rehman, Mohd Ziaur, 2023. "Spillovers and connectedness among BRICS stock markets, cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network," Emerging Markets Review, Elsevier, vol. 54(C).
    6. Mustafa Tevfik Kartal & Mustafa Kevser & Fatih Ayhan, 2023. "Asymmetric effects of global factors on return of cryptocurrencies by novel nonlinear quantile approaches," Economic Change and Restructuring, Springer, vol. 56(3), pages 1515-1535, June.
    7. Bonaparte, Yosef & Bernile, Gennaro, 2023. "A new “Wall Street Darling?” effects of regulation sentiment in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 52(C).
    8. Xia, Yufei & Sang, Chong & He, Lingyun & Wang, Ziyao, 2023. "The role of uncertainty index in forecasting volatility of Bitcoin: Fresh evidence from GARCH-MIDAS approach," Finance Research Letters, Elsevier, vol. 52(C).
    9. Abdülsamet Aça & Kemal Dinçer Dingeç, 2023. "NARDL Yönteminin Kripto Para Birimlerine Yönelik Bir Monte Carlo Simülasyon Analizi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(39), pages 37-48, December.

    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. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    2. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    3. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    4. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    5. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    6. 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.
    7. Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
    8. Auer, Benjamin R. & Rottmann, Horst, 2019. "Have capital market anomalies worldwide attenuated in the recent era of high liquidity and trading activity?," Journal of Economics and Business, Elsevier, vol. 103(C), pages 61-79.
    9. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    10. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    11. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    12. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    13. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    14. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Price delay and market frictions in cryptocurrency markets," Economics Letters, Elsevier, vol. 174(C), pages 39-41.
    15. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    16. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    17. Lauter, Tobias & Prokopczuk, Marcel, 2022. "Measuring commodity market quality," Journal of Banking & Finance, Elsevier, vol. 145(C).
    18. Vidal-Tomás, David, 2021. "The entry and exit dynamics of the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 58(C).
    19. Ince, Baris, 2022. "Liquidity components: Commonality in liquidity, underreaction, and equity returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    20. Wang, Pengfei & Zhang, Wei & Li, Xiao & Shen, Dehua, 2019. "Is cryptocurrency a hedge or a safe haven for international indices? A comprehensive and dynamic perspective," Finance Research Letters, Elsevier, vol. 31(C), pages 1-18.

    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:finlet:v:44:y:2022:i:c:s1544612321001124. 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/frl .

    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.