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Informed trading in the Bitcoin market

Author

Listed:
  • Feng, Wenjun
  • Wang, Yiming
  • Zhang, Zhengjun

Abstract

Bitcoin’s price sensitivity to the material events makes informed trading very profitable in this new market. We propose a novel indicator to assess informed trades ahead of cryptocurrency-related events. Using trade-level data of USD/BTC exchange rates, we find evidence of informed trading in the Bitcoin market prior to large events: Quantiles of the order sizes of buyer-initiated (seller-initiated) orders are abnormally high before large positive (negative) events, compared to the quantiles of seller-initiated (buyer-initiated) orders. When examining the timing of informed trades, we further notice that informed traders prefer to build their positions two days before large positive events and one day before large negative events. The profits of informed trading in the Bitcoin market are estimated to be considerably large.

Suggested Citation

  • Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
    • Handle: RePEc:eee:finlet:v:26:y:2018:i:c:p:63-70
    DOI: 10.1016/j.frl.2017.11.009
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    References listed on IDEAS

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    1. 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.
    2. Ormos, Mihály & Timotity, Dusán, 2016. "Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading," Finance Research Letters, Elsevier, vol. 19(C), pages 60-66.
    3. Jose M. Marin & Jacques P. Olivier, 2008. "The Dog That Did Not Bark: Insider Trading and Crashes," Journal of Finance, American Finance Association, vol. 63(5), pages 2429-2476, October.
    4. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
    5. David Easley & Robert F. Engle & Maureen O'Hara & Liuren Wu, 2008. "Time-Varying Arrival Rates of Informed and Uninformed Trades," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 171-207, Spring.
    6. Kim, Sangwan & Lim, Steve C., 2017. "Earnings comparability and informed trading," Finance Research Letters, Elsevier, vol. 20(C), pages 130-136.
    7. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    8. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    9. Fen-May Liou, 2008. "Fraudulent financial reporting detection and business failure prediction models: a comparison," Managerial Auditing Journal, Emerald Group Publishing, vol. 23(7), pages 650-662, July.
    10. Kim, Thomas, 2017. "On the transaction cost of Bitcoin," Finance Research Letters, Elsevier, vol. 23(C), pages 300-305.
    11. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    12. Steven L. Heston & Robert A. Korajczyk & Ronnie Sadka, 2010. "Intraday Patterns in the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1369-1407, August.
    13. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
    14. Harris, Terry, 2017. "Earnings announcements and quoted bid-ask spreads of U.S. Bank Holding Companies," Finance Research Letters, Elsevier, vol. 20(C), pages 223-228.
    15. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    16. Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
    17. Shen, Dehua & Li, Xiao & Zhang, Wei, 2017. "Baidu news coverage and its impacts on order imbalance and large-size trade of Chinese stocks," Finance Research Letters, Elsevier, vol. 23(C), pages 210-216.
    18. Bernile, Gennaro & Hu, Jianfeng & Tang, Yuehua, 2016. "Can information be locked up? Informed trading ahead of macro-news announcements," Journal of Financial Economics, Elsevier, vol. 121(3), pages 496-520.
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    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Informed trading;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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