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The effect of fragmentation in trading on market quality in the UK equity market

  • Lena Korber
  • Oliver Linton

    ()

    (Institute for Fiscal Studies and Cambridge University)

  • Michael Vogt

We investigate the effects of fragmentation in equity trading on the quality of the trading outcomes, specifically volatility, liquidity and volume. We use panel regression methods on a weekly dataset following the FTSE350 stocks over the period 2008-2011, which provides a lot of cross-sectional and time series variation in fragmentation. This period coincided with a great deal of turbulence in the UK equity markets which had multiple causes that need to be controlled for. To achieve this, we use a version of the common correlated effects estimator (Pesaran, 2006). One finding is that volatility is lower in a fragmented market when compared to a monopoly. Trading volume at the London Stock Exchange is lower too, but global trading volume is higher if order flow is fragmented across multiple venues. When separating overall fragmentation into visible fragmentation and dark reading, we find that the decline in LSE volume can be attributed to visible fragmentation, while the increase in global volume is due to dark trading.

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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP42/13.

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Date of creation: Aug 2013
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Handle: RePEc:ifs:cemmap:42/13
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  1. Kapetanios, George & Pesaran, M. Hashem & Yamagata, Takashi, 2006. "Panels with Nonstationary Multifactor Error Structures," IZA Discussion Papers 2243, Institute for the Study of Labor (IZA).
  2. G. Kapetanios & M. Hashem Pesaran & T. Yamagata, 2010. "Panels with nonstationary multifactor error structures," Post-Print peer-00768190, HAL.
  3. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
  4. Pagano, Marco, 1989. "Trading Volume and Asset Liquidity," The Quarterly Journal of Economics, MIT Press, vol. 104(2), pages 255-74, May.
  5. 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, 02.
  6. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  7. Biais, Bruno & Martimort, David & Rochet, Jean-Charles, 1998. "Competing Mechanisms in a Commun Value Environment," IDEI Working Papers 75, Institut d'Économie Industrielle (IDEI), Toulouse.
  8. 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.
  9. Boehmer, Beatrice & Boehmer, Ekkehart, 2003. "Trading your neighbor's ETFs: Competition or fragmentation?," Journal of Banking & Finance, Elsevier, vol. 27(9), pages 1667-1703, September.
  10. Sabrina Buti & Barbara Rindi & Ingrid M. Werner, 2011. "Dark Pool Trading Strategies," Working Papers 421, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  11. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
  12. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  13. Parameswaran Gopikrishnan & Vasiliki Plerou & Xavier Gabaix & H. Eugene Stanley, 2000. "Statistical Properties of Share Volume Traded in Financial Markets," Papers cond-mat/0008113, arXiv.org.
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