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On the dark side of the market: Identifying and analyzing hidden order placements

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  • Hautsch, Nikolaus
  • Huang, Ruihong

Abstract

Trading under limited pre-trade transparency becomes increasingly popular on financial markets. We provide first evidence on traders' use of (completely) hidden orders which might be placed even inside of the (displayed) bid-ask spread. Employing TotalView-ITCH data on order messages at NASDAQ, we propose a simple method to conduct statistical inference on the location of hidden depth and to test economic hypotheses. Analyzing a wide cross-section of stocks, we show that market conditions reflected by the (visible) bid-ask spread, (visible) depth, recent price movements and trading signals significantly affect the aggressiveness of 'dark' liquidity supply and thus the 'hidden spread'. Our evidence suggests that traders balance hidden order placements to (i) compete for the provision of (hidden) liquidity and (ii) protect themselves against adverse selection, front-running as well as 'hidden order detection strategies' used by high-frequency traders. Accordingly, our results show that hidden liquidity locations are predictable given the observable state of the market.

Suggested Citation

  • Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," SFB 649 Discussion Papers 2012-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2012-014
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    References listed on IDEAS

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    Cited by:

    1. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    2. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    3. Garvey, Ryan & Huang, Tao & Wu, Fei, 2016. "Why do traders choose dark markets?," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 12-28.
    4. Mahmoud Mahfouz & Tucker Balch & Manuela Veloso & Danilo Mandic, 2021. "Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets," Papers 2110.01325, arXiv.org, revised Oct 2021.
    5. Arzandeh, Mehdi & Frank, Julieta, 2017. "Price Discovery in Agricultural Futures Markets: Should We Look Beyond the Best Bid-Ask Spread?," Annual Meeting, 2017, June 18-21, Montreal, Canada 259344, Canadian Agricultural Economics Society.
    6. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.
    7. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    8. Quanbiao Shang & Teresa Serra & Philip Garcia & Mindy Mallory, 2021. "Looking under the surface: An analysis of iceberg orders in the U.S. agricultural futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 679-699, July.
    9. Degryse, Hans & Karagiannis, Nikolaos & Tombeur, Geoffrey & Wuyts, Gunther, 2021. "Two shades of opacity: Hidden orders and dark trading," Journal of Financial Intermediation, Elsevier, vol. 47(C).
    10. Arzandeh, Mehdi & Frank, Julieta, 2017. "The Information Content of the Limit Order Book," 7th Annual Canadian Agri-Food Policy Conference, January 11-13, 2017, Ottawa, ON 253251, Canadian Agricultural Economics Society.

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    More about this item

    Keywords

    limit order market; hidden liquidity; high-frequency trading; non-display order; iceberg orders;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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