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On the Dark Side of the Market: Identifying and Analyzing Hidden Order Placements

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  • Nikolaus Hautsch
  • Ruihong Huang

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

  • Nikolaus Hautsch & Ruihong Huang, 2012. "On the Dark Side of the Market: Identifying and Analyzing Hidden Order Placements," SFB 649 Discussion Papers SFB649DP2012-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2012-014
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    References listed on IDEAS

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    1. Moinas, Sophie, 2010. "Hidden Limit Orders and Liquidity in Order Driven Markets," IDEI Working Papers 600, Institut d'Économie Industrielle (IDEI), Toulouse.
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    5. Anthony Hall & Nikolaus Hautsch, 2006. "Order aggressiveness and order book dynamics," Empirical Economics, Springer, vol. 30(4), pages 973-1005, January.
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    9. Sabrina Buti & Barbara Rindi, 2011. "Undisclosed Orders and Optimal Submission Strategies in a Dynamic Limit Order Market," Working Papers 389, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. Rudy De Winne & Catherine D'hondt, 2007. "Hide-and-Seek in the Market: Placing and Detecting Hidden Orders," Review of Finance, European Finance Association, vol. 11(4), pages 663-692.
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    Citations

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    Cited by:

    1. 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.
    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. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.
    5. : Arie E. Gozluklu, 2012. "Pre-Trade Transparency and Informed Trading an Experimental Approach to Hidden Liquidity," Working Papers wpn12-05, Warwick Business School, Finance Group.

    More about this item

    Keywords

    limit order market; hidden liquidity; high-frequency trading; non-display order; iceberg orders;

    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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