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Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID

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  • Kohler, Alexander
  • von Wyss, Rico

Abstract

The implementation of MiFID lead to fragmentation of trading in European equities. We analyze information processing for a sample of Swiss stocks on the Swiss exchange and on Chi-X, the largest multilateral trading facility. According to Hasbrouck information shares, the determination of a leading market is not conclusively possible. By applying an autoregressive conditional intensity (ACI) model that explicitly takes the asynchronous structure of order arrivals into account, we find strong evidence that Chi-X is the leading market in terms of intensity based information shares.

Suggested Citation

  • Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    • Handle: RePEc:usg:sfwpfi:2012:09
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    References listed on IDEAS

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    1. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    2. Michael Chlistalla & Marco Lutat, 2011. "Competition in securities markets: the impact on liquidity," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(2), pages 149-172, June.
    3. Hupperets, Erik C. J. & Menkveld, Albert J., 2002. "Intraday analysis of market integration: Dutch blue chips traded in Amsterdam and New York," Journal of Financial Markets, Elsevier, vol. 5(1), pages 57-82, January.
    4. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    5. 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.
    6. 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.
    7. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    8. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
    9. Hans Degryse & Frank de Jong & Vincent van Kervel, 2015. "The Impact of Dark Trading and Visible Fragmentation on Market Quality," Review of Finance, European Finance Association, vol. 19(4), pages 1587-1622.
    10. Hall, Anthony D. & Hautsch, Nikolaus, 2007. "Modelling the buy and sell intensity in a limit order book market," Journal of Financial Markets, Elsevier, vol. 10(3), pages 249-286, August.
    11. Thierry Foucault & Albert J. Menkveld, 2008. "Competition for Order Flow and Smart Order Routing Systems," Journal of Finance, American Finance Association, vol. 63(1), pages 119-158, February.
    12. Andreas Storkenmaier & Martin Wagener & Christof Weinhardt, 2012. "Public information in fragmented markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(2), pages 179-215, June.
    13. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
    14. Hendershott, Terrence & Jones, Charles M., 2005. "Trade-through prohibitions and market quality," Journal of Financial Markets, Elsevier, vol. 8(1), pages 1-23, February.
    15. Yiuman Tse & Paramita Bandyopadhyay & Yang‐Pin Shen, 2006. "Intraday Price Discovery in the DJIA Index Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1572-1585, November.
    16. Joel Hasbrouck, 2003. "Intraday Price Formation in U.S. Equity Index Markets," Journal of Finance, American Finance Association, vol. 58(6), pages 2375-2400, December.
    17. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    18. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    19. G. Geoffrey Booth & Ji-Chai Lin & Teppo Martikainen & Yiuman Tse, 2002. "Trading and Pricing in Upstairs and Downstairs Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1111-1135.
    20. Kohler, Alexander & von Wyss, Rico, 2012. "Fragmentation in European Equity Markets and Market Quality – Evidence from the Analysis of Trade-Throughs," Working Papers on Finance 1210, University of St. Gallen, School of Finance.
    21. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    22. Yiuman Tse & Paramita Bandyopadhyay & Yang-Pin Shen, 2006. "Intraday Price Discovery in the DJIA Index Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9-10), pages 1572-1585.
    23. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    24. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
    25. Yan, Bingcheng & Zivot, Eric, 2010. "A structural analysis of price discovery measures," Journal of Financial Markets, Elsevier, vol. 13(1), pages 1-19, February.
    26. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
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    Cited by:

    1. Sabrina Buti & Barbara Rindi & Ingrid M. Werner, 2014. "Dark Pool Trading Strategies, Market Quality and Welfare," Working Papers 530, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

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    More about this item

    Keywords

    MiFID; Price Discovery; Multivariate Autoregressive Conditional Intensity.;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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