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Price discovery in tick time

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  • Frijns, Bart
  • Schotman, Peter

Abstract

This paper develops a tick time model for the quote setting dynamics on Nasdaq. The model decomposes quotes into an efficient price, asymmetric information and noise. Both the evolution of the efficient price and the information contents of quotes depend on quote durations. New measures for the contribution to price discovery are defined within this model. When aggregated to fixed calendar time intervals, they relate closely to Hasbrouck [Hasbrouck, Joel, 1995, One security, many markets: determining the contribution to price discovery, Journal of Finance 50, 1175-1199] information shares. Empirical results for 20 Nasdaq stocks indicate that ECNs, in particular Island, contribute most to price discovery for active stocks. For less active stocks, wholesale market makers contribute most.

Suggested Citation

  • Frijns, Bart & Schotman, Peter, 2009. "Price discovery in tick time," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 759-776, December.
    • Handle: RePEc:eee:empfin:v:16:y:2009:i:5:p:759-776
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    Cited by:

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    2. Hurvich, Cliiford & Wang, Yi, 2006. "A Pure-Jump Transaction-Level Price Model Yielding Cointegration, Leverage, and Nonsynchronous Trading Effects," MPRA Paper 1413, University Library of Munich, Germany.
    3. Lei Wu & Qingbin Meng & Kuan Xu, 2015. "'Slow-burn' spillover and 'fast and furious' contagion: a study of international stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 933-958, June.
    4. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    5. Wu, Lei & Liu, Chunlin & Meng, Qingbin & Zeng, Hongchao, 2018. "Price discovery in China's inter-bank bond market," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 84-98.
    6. Ozturk, Sait R. & van der Wel, Michel & van Dijk, Dick, 2017. "Intraday price discovery in fragmented markets," Journal of Financial Markets, Elsevier, vol. 32(C), pages 28-48.
    7. Otsubo, Yoichi, 2014. "International cross-listing and price discovery under trading concentration in the domestic market: Evidence from Japanese shares," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 36-51.
    8. Jahanshahloo, Hossein & Spokeviciute, Laima, 2021. "Time weighted price contribution," Finance Research Letters, Elsevier, vol. 43(C).
    9. Mizrach, Bruce & Neely, Christopher J., 2008. "Information shares in the US Treasury market," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1221-1233, July.
    10. Jondeau, Eric & Lahaye, Jérôme & Rockinger, Michael, 2015. "Estimating the price impact of trades in a high-frequency microstructure model with jumps," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 205-224.
    11. Gavious, Arieh & Kedar-Levy, Haim, 2013. "The speed of stock price discovery," Journal of Financial Intermediation, Elsevier, vol. 22(2), pages 245-258.
    12. Sait R. Ozturk & Michel van der Wel & Dick van Dijk, 2015. "Why do Pit-Hours outlive the Pit?," Tinbergen Institute Discussion Papers 15-082/III, Tinbergen Institute.
    13. Lei Wu & Kuan Xu & Qingbin Meng, 2021. "Information flow and price discovery dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 329-367, January.
    14. Kehrle, Kerstin & Peter, Franziska J., 2013. "Who moves first? An intensity-based measure for information flows across stock exchanges," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1629-1642.

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    More about this item

    Keywords

    Price discovery Tick time models Nasdaq Ultra-high frequency data Microstructure;

    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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