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Very fast money: High-frequency trading on the NASDAQ

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  • Carrion, Allen

Abstract

This paper provides evidence regarding high-frequency trader (HFT) trading performance, trading costs, and effects on market efficiency using a sample of NASDAQ trades and quotes that directly identifies HFT participation. I find that HFTs engage in successful intra-day market timing, spreads are wider when HFTs provide liquidity and tighter when HFTs take liquidity, and prices incorporate information from order flow and market-wide returns more efficiently on days when HFT participation is high.

Suggested Citation

  • Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    • Handle: RePEc:eee:finmar:v:16:y:2013:i:4:p:680-711
    DOI: 10.1016/j.finmar.2013.06.005
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    References listed on IDEAS

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    1. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    2. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    3. Bessembinder, Hendrik & Kaufman, Herbert M., 1997. "A Comparison of Trade Execution Costs for NYSE and NASDAQ-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(3), pages 287-310, September.
    4. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    5. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    6. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2011. "Recent trends in trading activity and market quality," Journal of Financial Economics, Elsevier, vol. 101(2), pages 243-263, August.
    7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    8. 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.
    9. Naik, Narayan Y. & Yadav, Pradeep K., 2003. "Do dealer firms manage inventory on a stock-by-stock or a portfolio basis?," Journal of Financial Economics, Elsevier, vol. 69(2), pages 325-353, August.
    10. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    11. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    12. Robert A. Jarrow & Philip Protter, 2012. "A Dysfunctional Role Of High Frequency Trading In Electronic Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-15.
    13. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    14. Huang, Roger D. & Stoll, Hans R., 1996. "Dealer versus auction markets: A paired comparison of execution costs on NASDAQ and the NYSE," Journal of Financial Economics, Elsevier, vol. 41(3), pages 313-357, July.
    15. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
    16. Hasabrouck, Joel & Sofianos, George, 1993. "The Trades of Market Makers: An Empirical Analysis of NYSE Specialists," Journal of Finance, American Finance Association, vol. 48(5), pages 1565-1593, December.
    17. Chung, Dennis & Hrazdil, Karel, 2010. "Liquidity and market efficiency: A large sample study," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2346-2357, October.
    18. Carole Comerton‐Forde & Terrence Hendershott & Charles M. Jones & Pamela C. Moulton & Mark S. Seasholes, 2010. "Time Variation in Liquidity: The Role of Market‐Maker Inventories and Revenues," Journal of Finance, American Finance Association, vol. 65(1), pages 295-331, February.
    19. Garman, Mark B., 1976. "Market microstructure," Journal of Financial Economics, Elsevier, vol. 3(3), pages 257-275, June.
    20. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    21. Ho, Thomas & Stoll, Hans R., 1981. "Optimal dealer pricing under transactions and return uncertainty," Journal of Financial Economics, Elsevier, vol. 9(1), pages 47-73, March.
    22. 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.
    23. Hans R. Stoll, 2000. "Presidential Address: Friction," Journal of Finance, American Finance Association, vol. 55(4), pages 1479-1514, August.
    24. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    25. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    26. Manaster, Steven & Mann, Steven C, 1996. "Life in the Pits: Competitive Market Making and Inventory Control," The Review of Financial Studies, Society for Financial Studies, vol. 9(3), pages 953-975.
    27. Mech, Timothy S., 1993. "Portfolio return autocorrelation," Journal of Financial Economics, Elsevier, vol. 34(3), pages 307-344, December.
    28. Bessembinder, Hendrik & Kaufman, Herbert M., 1997. "A cross-exchange comparison of execution costs and information flow for NYSE-listed stocks," Journal of Financial Economics, Elsevier, vol. 46(3), pages 293-319, December.
    29. repec:bla:jfinan:v:43:y:1988:i:1:p:97-112 is not listed on IDEAS
    30. Chung, Dennis Y. & Hrazdil, Karel, 2010. "Liquidity and market efficiency: Analysis of NASDAQ firms," Global Finance Journal, Elsevier, vol. 21(3), pages 262-274.
    31. Panayides, Marios A., 2007. "Affirmative obligations and market making with inventory," Journal of Financial Economics, Elsevier, vol. 86(2), pages 513-542, November.
    32. Brennan, Michael J & Jegadeesh, Narasimhan & Swaminathan, Bhaskaran, 1993. "Investment Analysis and the Adjustment of Stock Prices to Common Information," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 799-824.
    33. Bessembinder, Hendrik, 2003. "Trade Execution Costs and Market Quality after Decimalization," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(4), pages 747-777, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    High-frequency trading; Trading performance; Intraday return predictability; VWAP; Trading costs; Adverse selection; Market efficiency;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services

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