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The market impact of a limit order

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  • Hautsch, Nikolaus
  • Huang, Ruihong

Abstract

Despite their importance in modern electronic trading, virtually no systematic empirical evidence on the market impact of incoming orders is existing. We quantify the short-run and long-run price effect of posting a limit order by proposing a high-frequency cointegrated VAR model for ask and bid quotes and several levels of order book depth. Price impacts are estimated by means of appropriate impulse response functions. Analyzing order book data of 30 stocks traded at Euronext Amsterdam, we show that limit orders have significant market impacts and cause a dynamic (and typically asymmetric) rebalancing of the book. The strength and direction of quote and spread responses depend on the incoming orders' aggressiveness, their size and the state of the book. We show that the effects are qualitatively quite stable across the market. Cross-sectional variations in the magnitudes of price impacts are well explained by the underlying trading frequency and relative tick size.

Suggested Citation

  • Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
  • Handle: RePEc:zbw:cfswop:200923
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Yergeau, Gabriel, 2016. "Profitability and Market Quality of High Frequency Market-makers: An Empirical Investigation," Working Papers 16-3, HEC Montreal, Canada Research Chair in Risk Management.
    2. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    3. Fabrizio Pomponio & Frédéric Abergel, 2013. "Multiple-limit trades : empirical facts and application to lead-lag measures," Post-Print hal-00745317, HAL.
    4. Nikolaus Hautsch & Mark Podolskij, 2013. "Preaveraging-Based Estimation of Quadratic Variation in the Presence of Noise and Jumps: Theory, Implementation, and Empirical Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 165-183, April.
    5. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2733-2746, October.
    6. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    7. Comerton-Forde, Carole & Putniņš, Tālis J., 2015. "Dark trading and price discovery," Journal of Financial Economics, Elsevier, vol. 118(1), pages 70-92.
    8. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    9. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    10. Lo, Danny K. & Hall, Anthony D., 2015. "Resiliency of the limit order book," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 222-244.
    11. repec:eee:jfinec:v:125:y:2017:i:3:p:561-588 is not listed on IDEAS
    12. Cebiroğlu, Gökhan & Horst, Ulrich, 2015. "Optimal order display in limit order markets with liquidity competition," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 81-100.
    13. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    14. 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.
    15. Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity, volatility, and flights to safety in the U.S. treasury market: evidence from a new class of dynamic order book models," Staff Reports 590, Federal Reserve Bank of New York.
    16. repec:hal:wpaper:hal-00745317 is not listed on IDEAS
    17. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2010. "The Price Impact of Order Book Events," Papers 1011.6402, arXiv.org, revised Apr 2011.
    18. Cebiroglu, Gökhan & Hautsch, Nikolaus & Horst, Ulrich, 2014. "Order exposure and liquidity coordination: Does hidden liquidity harm price efficiency?," CFS Working Paper Series 468, Center for Financial Studies (CFS).
    19. Forsyth, P.A. & Kennedy, J.S. & Tse, S.T. & Windcliff, H., 2012. "Optimal trade execution: A mean quadratic variation approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1971-1991.
    20. Jose Blanchet & Xinyun Chen, 2013. "Continuous-time Modeling of Bid-Ask Spread and Price Dynamics in Limit Order Books," Papers 1310.1103, arXiv.org.
    21. Ulrich Horst & Dorte Kreher, 2015. "A weak law of large numbers for a limit order book model with fully state dependent order dynamics," Papers 1502.04359, arXiv.org, revised May 2016.
    22. Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
    23. Xue, Yi & Gençay, Ramazan, 2012. "Hierarchical information and the rate of information diffusion," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1372-1401.
    24. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 22.
    25. Gökhan Cebiroglu & Ulrich Horst, 2012. "Hidden Liquidity: Determinants and Impact," SFB 649 Discussion Papers SFB649DP2012-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    More about this item

    Keywords

    Price Impact; Limit Order; Impulse Response Function; Cointegration;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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