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Intraday Price Discovery in Fragmented Markets

Author

Listed:
  • Sait Ozturk

    (Econometric Institute, Erasmus University Rotterdam)

  • Michel van der Wel

    (Econometric Institute, Erasmus University Rotterdam)

Abstract

For many assets, trading is fragmented across multiple exchanges. Price discovery measures summarize the informativeness of trading on each venue for discovering the asset’s true underlying value. We explore intraday variation in price discovery using a structural model with time-varying parameters that can be estimated with state space techniques. An application to the Expedia stock demonstrates intraday variation, to the extent that the overall dominant trading venue (NASDAQ) does not lead the entire day. Spreads, the number of trades and volatility can explain almost half of the intraday variation in information shares.

Suggested Citation

  • Sait Ozturk & Michel van der Wel, 2014. "Intraday Price Discovery in Fragmented Markets," Tinbergen Institute Discussion Papers 14-027/III, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20140027
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    References listed on IDEAS

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    1. Slezak, Steve L, 1994. " A Theory of the Dynamics of Security Returns around Market Closures," Journal of Finance, American Finance Association, vol. 49(4), pages 1163-1211, September.
    2. Hasbrouck, Joel, 2004. "Liquidity in the Futures Pits: Inferring Market Dynamics from Incomplete Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 305-326, June.
    3. Wood, Robert A & McInish, Thomas H & Ord, J Keith, 1985. " An Investigation of Transactions Data for NYSE Stocks," Journal of Finance, American Finance Association, vol. 40(3), pages 723-739, July.
    4. Oleg Korenok & Bruce Mizrach & Stanislav Radchenko, 2011. "A Structural Approach To Information Shares," Departmental Working Papers 201130, Rutgers University, Department of Economics.
    5. Joon Chae, 2005. "Trading Volume, Information Asymmetry, and Timing Information," Journal of Finance, American Finance Association, vol. 60(1), pages 413-442, February.
    6. Torben G. Andersen, 2001. "Variance-ratio Statistics and High-frequency Data: Testing for Changes in Intraday Volatility Patterns," Journal of Finance, American Finance Association, vol. 56(1), pages 305-327, February.
    7. Foster, F Douglas & Viswanathan, S, 1993. " Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models," Journal of Finance, American Finance Association, vol. 48(1), pages 187-211, March.
    8. Frank De Jong & Peter C. Schotman, 2010. "Price Discovery in Fragmented Markets," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(1), pages 1-28, Winter.
    9. Gonzalo, Jesus & Granger, Clive W J, 1995. "Estimation of Common Long-Memory Components in Cointegrated Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 27-35, January.
    10. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    11. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.
    12. de Jong, Frank, 2002. "Measures of contributions to price discovery: a comparison," Journal of Financial Markets, Elsevier, vol. 5(3), pages 323-327, July.
    13. Christian Upper & Thomas Werner, 2007. "The tail wags the dog: time-varying information shares in the Bund market," BIS Working Papers 224, Bank for International Settlements.
    14. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.
    15. Frijns, Bart & Schotman, Peter, 2009. "Price discovery in tick time," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 759-776, December.
    16. Sugato Chakravarty & Huseyin Gulen & Stewart Mayhew, 2004. "Informed Trading in Stock and Option Markets," Journal of Finance, American Finance Association, vol. 59(3), pages 1235-1258, June.
    17. deB. Harris, Frederick H. & McInish, Thomas H. & Wood, Robert A., 2002. "Security price adjustment across exchanges: an investigation of common factor components for Dow stocks," Journal of Financial Markets, Elsevier, vol. 5(3), pages 277-308, July.
    18. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    19. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    20. 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.
    21. Hee-Joon Ahn, 2001. "Limit Orders, Depth, and Volatility: Evidence from the Stock Exchange of Hong Kong," Journal of Finance, American Finance Association, vol. 56(2), pages 767-788, April.
    22. Grammig, Joachim & Peter, Franziska J., 2013. "Telltale Tails: A New Approach to Estimating Unique Market Information Shares," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(02), pages 459-488, April.
    23. 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.
    24. Lockwood, Larry J & Linn, Scott C, 1990. " An Examination of Stock Market Return Volatility during Overnight and Intraday Periods, 1964-1989," Journal of Finance, American Finance Association, vol. 45(2), pages 591-601, June.
    25. Lehmann, Bruce N., 2002. "Some desiderata for the measurement of price discovery across markets," Journal of Financial Markets, Elsevier, vol. 5(3), pages 259-276, July.
    26. David A. Hsieh & Allan W. Kleidon, 1996. "Bid-Ask Spreads in Foreign Exchange Markets: Implications for Models of Asymmetric Information," NBER Chapters,in: The Microstructure of Foreign Exchange Markets, pages 41-72 National Bureau of Economic Research, Inc.
    27. de Jong, F.C.J.M. & Schotman, P.C., 2010. "Price discovery in fragmented markets," Other publications TiSEM 4650a9e7-c4cf-41cf-a771-e, Tilburg University, School of Economics and Management.
    28. 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.
    29. Yan, Bingcheng & Zivot, Eric, 2010. "A structural analysis of price discovery measures," Journal of Financial Markets, Elsevier, vol. 13(1), pages 1-19, February.
    30. Baillie, Richard T. & Geoffrey Booth, G. & Tse, Yiuman & Zabotina, Tatyana, 2002. "Price discovery and common factor models," Journal of Financial Markets, Elsevier, vol. 5(3), pages 309-321, July.
    31. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    32. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
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    Citations

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    Cited by:

    1. Gustavo Fruet Dias & Marcelo Fernandes & Cristina M. Scherrer, 2016. "Component shares in continuous time," CREATES Research Papers 2016-25, Department of Economics and Business Economics, Aarhus University.
    2. Takaki Hayashi & Yuta Koike, 2017. "Multi-scale analysis of lead-lag relationships in high-frequency financial markets," Papers 1708.03992, arXiv.org, revised Feb 2018.
    3. Dias, Gustavo Fruet & Fernandes, Marcelo & Scherrer, Cristina Mabel, 2017. "Improving on daily measures of price discovery," Textos para discussão 444, FGV/EESP - Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).

    More about this item

    Keywords

    High-frequency data; Market microstructure; Price Discovery; Kalman filter;

    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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