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A Continuous-Time Measurement of the Buy-Sell Pressure in a Limit Order Book Market

Author

Listed:
  • Anthony D. Hall

    (School of Finance and Economics, University of Technology, Sydney)

  • Nikolaus Hautsch

    (Institute of Economics, University of Copenhagen)

Abstract

In this paper, we investigate the buy and sell arrival process in a limit order book market. Using an intensity framework allows to estimate the simultaneous buy and sell intensity and to derive a continuous-time measure for the buy-sell pressure in the market. Based on limit order book data from the Australian Stock Exchange (ASX), we show that the buy-sell pressure is particularly influenced by recent market and limit orders and the current depth in the ask and bid queue. We find evidence for the hypothesis that traders use order book information in order to infer from the price setting behavior of market participants. Furthermore, our results indicate that the buy-sell pressure is clearly predictable and is a significant determinant of trade-to-trade returns and volatility.

Suggested Citation

  • Anthony D. Hall & Nikolaus Hautsch, 2004. "A Continuous-Time Measurement of the Buy-Sell Pressure in a Limit Order Book Market," FRU Working Papers 2004/03, University of Copenhagen. Department of Economics. Finance Research Unit.
  • Handle: RePEc:kud:kuiefr:200403
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    Citations

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    Cited by:

    1. Bowsher, Clive G., 2007. "Modelling security market events in continuous time: Intensity based, multivariate point process models," Journal of Econometrics, Elsevier, vol. 141(2), pages 876-912, December.
    2. Anthony D. Hall & Nikolaus Hautsch, 2008. "Order aggressiveness and order book dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 133-165, Springer.
    3. Asani Sarkar & Robert A. Schwartz, 2009. "Market Sidedness: Insights into Motives for Trade Initiation," Journal of Finance, American Finance Association, vol. 64(1), pages 375-423, February.
    4. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    5. Asani Sarkar & Robert A. Schwartz, 2006. "Two-sided markets and intertemporal trade clustering: insights into trading motives," Staff Reports 246, Federal Reserve Bank of New York.
    6. Andrea Consiglio & Valerio Lacagnina & Annalisa Russino, 2005. "A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 71-87.
    7. Wing Lon Ng, 2010. "Dynamic Order Submission And Herding Behavior In Electronic Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 27-43, March.
    8. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2008. "Order Placement Strategies In A Pure Limit Order Book Market," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 31(2), pages 113-140, June.
    9. Voev, Valeri, 2006. "A trade-by-trade surprise measure and its relation to observed spreads on the NYSE," CoFE Discussion Papers 06/03, University of Konstanz, Center of Finance and Econometrics (CoFE).

    More about this item

    Keywords

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    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • 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
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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