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Price clustering in Bitcoin

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  • 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
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    References listed on IDEAS

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    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," 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.
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    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

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