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Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements

Author

Listed:
  • Martin L. Scholtus

    (Erasmus University Rotterdam)

  • Dick van Dijk

    (Erasmus University Rotterdam)

  • Bart Frijns

    (Auckland University of Technology)

Abstract

This discussion paper resulted in a publication in the 'Journal of Banking and Finance', 2014, 38, 89-105. This paper documents that speed is crucially important for high frequency trading strategies based on U.S. macroeconomic news releases. Using order level data of the highly liquid S&P500 ETF traded on NASDAQ from January 6, 2009, to December 12, 2011, we find that a delay of 300 milliseconds (1 second) significantly reduces returns by 3.08% (7.33%) compared to instantaneous execution over all announcements in the sample. This reduction is stronger in case of high impact news and on days with high volatility. In addition, we assess the effect of algorithmic trading on market quality around macroeconomic news. Increases in algorithmic trading activity have a positive (mixed) effect on market quality measures when we use algorithmic trading proxies that capture the top of the orderbook (full orderbook).

Suggested Citation

  • Martin L. Scholtus & Dick van Dijk & Bart Frijns, 2012. "Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements," Tinbergen Institute Discussion Papers 12-121/III, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20120121
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    References listed on IDEAS

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    1. Pearce, Douglas K & Roley, V Vance, 1985. "Stock Prices and Economic News," The Journal of Business, University of Chicago Press, vol. 58(1), pages 49-67, January.
    2. Bloomfield, Robert & O'Hara, Maureen & Saar, Gideon, 2005. "The "make or take" decision in an electronic market: Evidence on the evolution of liquidity," Journal of Financial Economics, Elsevier, vol. 75(1), pages 165-199, January.
    3. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2013. "Liquidity Cycles and Make/Take Fees in Electronic Markets," Journal of Finance, American Finance Association, vol. 68(1), pages 299-341, February.
    4. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, vol. 2(2), pages 99-134, May.
    5. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
    6. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    7. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    8. Birz, Gene & Lott Jr., John R., 2011. "The effect of macroeconomic news on stock returns: New evidence from newspaper coverage," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2791-2800, November.
    9. Jain, Prem C, 1988. "Response of Hourly Stock Prices and Trading Volume to Economic News," The Journal of Business, University of Chicago Press, vol. 61(2), pages 219-231, April.
    10. Hee‐Joon Ahn & Kee‐Hong Bae & Kalok Chan, 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.
    11. 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.
    12. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    13. Greg Adams & Grant McQueen & Robert Wood, 2004. "The Effects of Inflation News on High Frequency Stock Returns," The Journal of Business, University of Chicago Press, vol. 77(3), pages 547-574, July.
    14. John H. Boyd & Jian Hu & Ravi Jagannathan, 2005. "The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks," Journal of Finance, American Finance Association, vol. 60(2), pages 649-672, April.
    15. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    16. Hardouvelis, Gikas A., 1987. "Macroeconomic information and stock prices," Journal of Economics and Business, Elsevier, vol. 39(2), pages 131-140, May.
    17. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November.
    18. Menkhoff, Lukas & Osler, Carol L. & Schmeling, Maik, 2010. "Limit-order submission strategies under asymmetric information," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2665-2677, November.
    19. Fong, Kingsley Y.L. & Liu, Wai-Man, 2010. "Limit order revisions," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1873-1885, August.
    20. Erenburg, Grigori & Lasser, Dennis, 2009. "Electronic limit order book and order submission choice around macroeconomic news," Review of Financial Economics, Elsevier, vol. 18(4), pages 172-182, October.
    21. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    22. Handa, Puneet & Schwartz, Robert A, 1996. "Limit Order Trading," Journal of Finance, American Finance Association, vol. 51(5), pages 1835-1861, December.
    23. 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.
    24. Erenburg, Grigori & Kurov, Alexander & Lasser, Dennis J., 2006. "Trading around macroeconomic announcements: Are all traders created equal?," Journal of Financial Intermediation, Elsevier, vol. 15(4), pages 470-493, October.
    25. Liu, Wai-Man, 2009. "Monitoring and limit order submission risks," Journal of Financial Markets, Elsevier, vol. 12(1), pages 107-141, February.
    26. Michael J. Fleming & Eli M. Remolona, 1999. "Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information," Journal of Finance, American Finance Association, vol. 54(5), pages 1901-1915, October.
    27. McQueen, Grant & Roley, V Vance, 1993. "Stock Prices, News, and Business Conditions," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 683-707.
    28. Martin Scholtus & Dick van Dijk, 2012. "High-Frequency Technical Trading: The Importance of Speed," Tinbergen Institute Discussion Papers 12-018/4, Tinbergen Institute.
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    More about this item

    Keywords

    Macroeconomic News; High Frequency Trading; Latency Costs; Market Activity; Event-Based Trading;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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