IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2109.12142.html
   My bibliography  Save this paper

Periodicity in Cryptocurrency Volatility and Liquidity

Author

Listed:
  • Peter Reinhard Hansen
  • Chan Kim
  • Wade Kimbrough

Abstract

We study recurrent patterns in volatility and volume for major cryptocurrencies, Bitcoin and Ether, using data from two centralized exchanges (Coinbase Pro and Binance) and a decentralized exchange (Uniswap V2). We find systematic patterns in both volatility and volume across day-of-the-week, hour-of-the-day, and within the hour. These patterns have grown stronger over the years and can be related to algorithmic trading and funding times in futures markets. We also document that price formation mainly takes place on the centralized exchanges while price adjustments on the decentralized exchanges can be sluggish.

Suggested Citation

  • Peter Reinhard Hansen & Chan Kim & Wade Kimbrough, 2021. "Periodicity in Cryptocurrency Volatility and Liquidity," Papers 2109.12142, arXiv.org, revised Nov 2021.
  • Handle: RePEc:arx:papers:2109.12142
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2109.12142
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    2. 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.
    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. Yufan Chen & Lan Wu & Renyuan Xu & Ruixun Zhang, 2024. "Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players," Papers 2408.09505, arXiv.org.
    2. Namryoung Lee, 2024. "Joint Impact of Market Volatility and Cryptocurrency Holdings on Corporate Liquidity: A Comparative Analysis of Cryptocurrency Exchanges and Other Firms," JRFM, MDPI, vol. 17(9), pages 1-20, September.

    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. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    3. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    4. Wei, Yu & Wang, Yizhi & Vigne, Samuel A. & Ma, Zhenyu, 2023. "Alarming contagion effects: The dangerous ripple effect of extreme price spillovers across crude oil, carbon emission allowance, and agriculture futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    5. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    6. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    7. Yue-Jun Zhang & Han Zhang, 2023. "Volatility Forecasting of Crude Oil Market: Which Structural Change Based GARCH Models have Better Performance?," The Energy Journal, , vol. 44(1), pages 175-194, January.
    8. Hartwell, Christopher A., 2014. "The impact of institutional volatility on financial volatility in transition economies : a GARCH family approach," BOFIT Discussion Papers 6/2014, Bank of Finland, Institute for Economies in Transition.
    9. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    10. Jin Guo & Tetsuji Tanaka, 2020. "The Effectiveness of Self-Sufficiency Policy: International Price Transmissions in Beef Markets," Sustainability, MDPI, vol. 12(15), pages 1-23, July.
    11. Helmut Lütkepohl & Thore Schlaak, 2018. "Choosing Between Different Time‐Varying Volatility Models for Structural Vector Autoregressive Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(4), pages 715-735, August.
    12. Sabbaghi, Omid & Sabbaghi, Navid, 2011. "Carbon Financial Instruments, thin trading, and volatility: Evidence from the Chicago Climate Exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 399-407.
    13. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    14. David E. Allen & Michael McAleer & Marcel Scharth, 2009. "Realized Volatility Risk," CIRJE F-Series CIRJE-F-693, CIRJE, Faculty of Economics, University of Tokyo.
    15. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    16. Javed Farrukh & Podgórski Krzysztof, 2017. "Tail Behavior and Dependence Structure in the APARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-48, July.
    17. Massimiliano Marzo & Paolo Zagaglia, 2010. "Volatility forecasting for crude oil futures," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
    18. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," JRFM, MDPI, vol. 7(2), pages 1-30, June.
    19. Harry-Paul Vander Elst, 2015. "FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility," Working Papers ECARES ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
    20. 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).

    More about this item

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2109.12142. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.