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Execution Costs of Institutional Equity Orders

Author

Listed:
  • Jones, C.M.
  • Lipson, M.L.

Abstract

We compare institutional execution costs across the major U.S. exchanges using a sample of institutional equity orders in firms that switch exchanges. Execution costs including commissions are essentially indistinguishable across these exchanges. We also find the fraction of trading volume from momentum traders is greater on the NYSE than either the Nasdaq or AMEX and that orders are more likely to be worked by an institution's trading desk on the NYSE than on the Nasdaq. These results suggest that institutions actively manage execution strategies, taking into account characteristics of the markets in which they trade.

Suggested Citation

  • Jones, C.M. & Lipson, M.L., 1999. "Execution Costs of Institutional Equity Orders," Papers 99-1, Columbia - Graduate School of Business.
    • Handle: RePEc:fth:colubu:99-1
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    Cited by:

    1. Harald Hau, 2006. "The Role of Transaction Costs for Financial Volatility: Evidence from the Paris Bourse," Journal of the European Economic Association, MIT Press, vol. 4(4), pages 862-890, June.
    2. Corwin, Shane A. & Lipson, Marc L., 2011. "Order characteristics and the sources of commonality in prices and liquidity," Journal of Financial Markets, Elsevier, vol. 14(1), pages 47-81, February.
    3. John M.R. Chalmers & Roger M. Edelen & Gregory B. Kadlec, "undated". "Mutual fund trading costs," Rodney L. White Center for Financial Research Working Papers 27-99, Wharton School Rodney L. White Center for Financial Research.
    4. Jones, Charles M. & Lipson, Marc L., 2001. "Sixteenths: direct evidence on institutional execution costs," Journal of Financial Economics, Elsevier, vol. 59(2), pages 253-278, February.
    5. John M.R. Chalmers & Roger M. Edelen & Gregory B. Kadlec, 1999. "Transaction-cost Expenditures and the Relative Performance of Mutual Funds," Center for Financial Institutions Working Papers 00-02, Wharton School Center for Financial Institutions, University of Pennsylvania.
    6. Robert Almgren, 2003. "Optimal execution with nonlinear impact functions and trading-enhanced risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 1-18.
    7. Broom, Kevin D. & Van Ness, Robert A. & Warr, Richard S., 2007. "Cubes to quads: The move of QQQ from AMEX to NASDAQ," Journal of Economics and Business, Elsevier, vol. 59(6), pages 520-535.
    8. Ronen, Tavy & Weaver, Daniel G., 2001. "'Teenies' anyone?," Journal of Financial Markets, Elsevier, vol. 4(3), pages 231-260, June.
    9. Chakravarty, Sugato & Panchapagesan, Venkatesh & Wood, Robert A., 2005. "Did decimalization hurt institutional investors?," Journal of Financial Markets, Elsevier, vol. 8(4), pages 400-420, November.
    10. Massmiliano, Marzo & Daniele, Ritelli & Paolo, Zagaglia, 2011. "Optimal trading execution with nonlinear market impact: an alternative solution method," MPRA Paper 35393, University Library of Munich, Germany.
    11. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    12. Naes, Randi & Odegaard, Bernt Arne, 2006. "Equity trading by institutional investors: To cross or not to cross?," Journal of Financial Markets, Elsevier, vol. 9(2), pages 79-99, May.
    13. Martin D. D. Evans & Richard K. Lyons, 2017. "How is Macro News Transmitted to Exchange Rates?," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 14, pages 547-596, World Scientific Publishing Co. Pte. Ltd..
    14. Nan Qin & Vijay Singal, 2015. "Indexing and Stock Price Efficiency," Financial Management, Financial Management Association International, vol. 44(4), pages 875-904, October.
    15. Roger M. Edelen & Jerold B. Warner, "undated". "Aggregate Prixe Effects of Institutional Trading: A Study of Mutual Fund Flow and Market Returns," Rodney L. White Center for Financial Research Working Papers 26-99, Wharton School Rodney L. White Center for Financial Research.
    16. Griffith, Todd G. & Roseman, Brian S., 2019. "Making cents of tick sizes: The effect of the 2016 U.S. SEC tick size pilot on limit order book liquidity," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 104-121.
    17. Hu, Gang, 2009. "Measures of implicit trading costs and buy-sell asymmetry," Journal of Financial Markets, Elsevier, vol. 12(3), pages 418-437, August.
    18. Frino, Alex & Gallagher, David R. & Oetomo, Teddy N., 2006. "Further analysis of the liquidity and information components of institutional orders: Active versus passive funds," Pacific-Basin Finance Journal, Elsevier, vol. 14(5), pages 439-452, November.
    19. Levi, Shai & Zhang, Xiao-Jun, 2015. "Asymmetric decrease in liquidity trading before earnings announcements and the announcement return premium," Journal of Financial Economics, Elsevier, vol. 118(2), pages 383-398.
    20. Naes, Randi & Skjeltorp, Johannes A., 2003. "Equity trading by institutional investors: Evidence on order submission strategies," Journal of Banking & Finance, Elsevier, vol. 27(9), pages 1779-1817, September.
    21. Sagade, Satchit & Scharnowski, Stefan & Westheide, Christian, 2022. "Broker colocation and the execution costs of customer and proprietary orders," SAFE Working Paper Series 366, Leibniz Institute for Financial Research SAFE.
    22. Bennett, Paul & Wei, Li, 2006. "Market structure, fragmentation, and market quality," Journal of Financial Markets, Elsevier, vol. 9(1), pages 49-78, February.
    23. Edelen, Roger M. & Warner, Jerold B., 2001. "Aggregate price effects of institutional trading: a study of mutual fund flow and market returns," Journal of Financial Economics, Elsevier, vol. 59(2), pages 195-220, February.
    24. Lipson, Marc L., 2003. "Market microstructure and corporate finance," Journal of Corporate Finance, Elsevier, vol. 9(4), pages 377-384, September.

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    More about this item

    Keywords

    FINANCIAL MARKET;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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