IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v159y2017icp145-148.html
   My bibliography  Save this article

Price clustering in Bitcoin

Author

Listed:
  • Urquhart, Andrew

Abstract

Investor and media attention in Bitcoin has increased substantially in recently years, reflected by the incredible surge in news articles and considerable rise in the price of Bitcoin. Given the increased attention, there little is known about the behaviour of Bitcoin prices and therefore we add to the literature by studying price clustering. We find significant evidence of clustering at round numbers, with over 10% of prices ending with 00 decimals compared to other variations but there is no significant pattern of returns after the round number. We also support the negotiation hypothesis of Harris (1991) by showing that price and volume have a significant positive relationship with price clustering at whole numbers.

Suggested Citation

  • Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
  • Handle: RePEc:eee:ecolet:v:159:y:2017:i:c:p:145-148
    DOI: 10.1016/j.econlet.2017.07.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517303233
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2017.07.035?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. Brown, Alasdair & Yang, Fuyu, 2016. "Limited cognition and clustered asset prices: Evidence from betting markets," Journal of Financial Markets, Elsevier, vol. 29(C), pages 27-46.
    2. Robert I. Webb & Jason Mitchell, 2001. "Clustering and psychological barriers: the importance of numbers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(5), pages 395-428, May.
    3. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    4. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    5. Sonnemans, Joep, 2006. "Price clustering and natural resistance points in the Dutch stock market: A natural experiment," European Economic Review, Elsevier, vol. 50(8), pages 1937-1950, November.
    6. Clifford A. Ball & Walter N. Torous & Adrian E. Tschoegl, 1985. "The degree of price resolution: The case of the gold market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(1), pages 29-43, March.
    7. Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 389-415.
    8. David L. Ikenberry & James P. Weston, 2008. "Clustering in US Stock Prices after Decimalisation," European Financial Management, European Financial Management Association, vol. 14(1), pages 30-54, January.
    9. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    10. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    11. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
    12. Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan, 2011. "Investigating price clustering in the oil futures market," Applied Energy, Elsevier, vol. 88(1), pages 397-402, January.
    13. Riccardo Curcio & Charles Goodhart, 1991. "The Clustering of Bid/Ask Prices and the Spread in the Foreign Exchange Market," FMG Discussion Papers dp110, Financial Markets Group.
    14. Sopranzetti, Ben J. & Datar, Vinay, 2002. "Price clustering in foreign exchange spot markets," Journal of Financial Markets, Elsevier, vol. 5(4), pages 411-417, October.
    15. Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan & D'Rosario, Michael, 2011. "Share price clustering in Mexico," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 113-119, April.
    16. Bharati, Rakesh & Crain, Susan J. & Kaminski, Vincent, 2012. "Clustering in crude oil prices and the target pricing zone hypothesis," Energy Economics, Elsevier, vol. 34(4), pages 1115-1123.
    17. Aslı Aşçıoğlu & Carole Comerton‐Forde & Thomas H. McInish, 2007. "Price Clustering on the Tokyo Stock Exchange," The Financial Review, Eastern Finance Association, vol. 42(2), pages 289-301, May.
    18. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.
    19. Ahn, Hee-Joon & Cai, Jun & Cheung, Yan Leung, 2005. "Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong," Journal of Financial Markets, Elsevier, vol. 8(4), pages 421-451, November.
    Full references (including those not matched with items on IDEAS)

    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. Donglian Ma & Hisashi Tanizaki, 2022. "Intraday patterns of price clustering in Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    2. Telli, Şahin & Zhao, Xufeng, 2023. "Clustering in Bitcoin balance," Finance Research Letters, Elsevier, vol. 55(PA).
    3. Li, Xin & Li, Shenghong & Xu, Chong, 2020. "Price clustering in Bitcoin market—An extension," Finance Research Letters, Elsevier, vol. 32(C).
    4. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    5. Ahmed S. Baig & Benjamin M. Blau & R. Jared DeLisle, 2022. "Does mutual fund ownership reduce stock price clustering? Evidence from active and index funds," Review of Quantitative Finance and Accounting, Springer, vol. 58(2), pages 615-647, February.
    6. Quiroga-Garcia, Raquel & Pariente-Martinez, Natalia & Arenas-Parra, Mar, 2022. "Evidence for round number effects in cryptocurrencies prices," Finance Research Letters, Elsevier, vol. 47(PB).
    7. Das, Sougata & Kadapakkam, Palani-Rajan, 2020. "Machine over Mind? Stock price clustering in the era of algorithmic trading," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    8. Narayan, Paresh Kumar & Smyth, Russell, 2013. "Has political instability contributed to price clustering on Fiji's stock market?," Journal of Asian Economics, Elsevier, vol. 28(C), pages 125-130.
    9. Robert Brooks & Edwyna Harris & Yovina Joymungul, 2013. "Price clustering in Australian water markets," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 677-685, February.
    10. Júlio Lobão & Luís Pacheco & Luís Alves, 2019. "Price Clustering in Bank Stocks During the Global Financial Crisis," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 66(4), pages 465-486, December.
    11. 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.
    12. Hu, Bill & McInish, Thomas & Miller, Jonathan & Zeng, Li, 2019. "Intraday price behavior of cryptocurrencies," Finance Research Letters, Elsevier, vol. 28(C), pages 337-342.
    13. Berk, Ales S. & Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2017. "Psychological price barriers in frontier equities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 1-14.
    14. 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.
    15. Christos Alexakis & Mark Cummins & Michael Dowling & Vasileios Pappas, 2018. "A High-Frequency Analysis of Price Resolution and Pricing Barriers in Equities on the Adoption of a New Currency," Post-Print hal-01994666, HAL.
    16. Huthaifa Alqaralleh & Alaa Adden Abuhommous & Ahmad Alsaraireh, 2020. "Modelling and Forecasting the Volatility of Cryptocurrencies: A Comparison of Nonlinear GARCH-Type Models," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 346-356, July.
    17. 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.
    18. Brown, Philip & Mitchell, Jason, 2008. "Culture and stock price clustering: Evidence from The Peoples' Republic of China," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 95-120, January.
    19. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    20. Verousis, Thanos & ap Gwilym, Owain, 2013. "Trade size clustering and the cost of trading at the London Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 91-102.

    More about this item

    Keywords

    Bitcoin; Price clustering; Cryptocurrency;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:ecolet:v:159:y:2017:i:c:p:145-148. 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/ecolet .

    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.