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

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  • Lena Boneva (Körber)
  • Oliver Linton
  • Michael Vogt

Abstract

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.

Suggested Citation

  • Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "The effect of fragmentation in trading on market quality in the UK equity market," CeMMAP working papers 42/13, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:42/13
    DOI: 10.1920/wp.cem.2013.4213
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    References listed on IDEAS

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    1. 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.
    2. Marco Pagano, 1989. "Trading Volume and Asset Liquidity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(2), pages 255-274.
    3. 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, July.
    4. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 735-765.
    5. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    6. 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.
    7. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of Semiparametric Models when the Criterion Function Is Not Smooth," Econometrica, Econometric Society, vol. 71(5), pages 1591-1608, September.
    8. 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.
    9. Sabrina Buti & Barbara Rindi & Ingrid M. Werner, 2010. "Dynamic Dark Pool Trading Strategies in Limit Order Markets," Working Papers 371, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. 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.
    11. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    12. repec:dau:papers:123456789/7685 is not listed on IDEAS
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