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Computerized and High-Frequency Trading

Author

Listed:
  • Michael Goldstein
  • Michael A. Goldstein
  • Pavitra Kumar
  • Frank C. Graves

Abstract

The use of computers to execute trades, often with very low latency, has increased over time, resulting in a variety of computer algorithms executing electronically targeted trading strategies at high speed. We describe the evolution of increasingly fast automated trading over the past decade and some key features of its associated practices, strategies, and apparent profitability. We also survey and contrast several studies on the impacts of such high-speed trading on the performance of securities markets. Finally, we examine some of the regulatory questions surrounding the need, if any, for safeguards over the fairness and risks of high-speed, computerized trading.

Suggested Citation

  • Michael Goldstein & Michael A. Goldstein & Pavitra Kumar & Frank C. Graves, 2014. "Computerized and High-Frequency Trading," The Financial Review, Eastern Finance Association, vol. 49(2), pages 177-202, May.
    • Handle: RePEc:bla:finrev:v:49:y:2014:i:2:p:177-202
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    File URL: http://hdl.handle.net/10.1111/fire.12031
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    Citations

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    Cited by:

    1. Vasilios Mavroudis, 2019. "Market Manipulation as a Security Problem," Papers 1903.12458, arXiv.org.
    2. Poutré, Cédric & Dionne, Georges & Yergeau, Gabriel, 2023. "International high-frequency arbitrage for cross-listed stocks," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    4. Brian F Tivnan & David Rushing Dewhurst & Colin M Van Oort & John H Ring IV & Tyler J Gray & Brendan F Tivnan & Matthew T K Koehler & Matthew T McMahon & David M Slater & Jason G Veneman & Christopher, 2020. "Fragmentation and inefficiencies in US equity markets: Evidence from the Dow 30," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-24, January.
    5. Manahov, Viktor, 2016. "A note on the relationship between high-frequency trading and latency arbitrage," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 281-296.
    6. Viktor Manahov, 2018. "The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming," Annals of Operations Research, Springer, vol. 260(1), pages 321-352, January.
    7. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    8. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    9. Bäumer, Marcus, 2020. "What matters to investment professionals in decision making? The role of soft factors in stock selection," EIKV-Schriftenreihe zum Wissens- und Wertemanagement, European Institute for Knowledge & Value Management (EIKV), Luxembourg, volume 44, number 44.
    10. Ben Omrane, Walid & Tao, Yusi & Welch, Robert, 2017. "Scheduled macro-news effects on a Euro/US dollar limit order book around the 2008 financial crisis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 9-30.
    11. Henryk Gurgul & Robert Syrek, 2016. "The logarithmic ACD model: The microstructure of the German and Polish stock markets," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 17(1), pages 77-92.
    12. Wang, Qin & Zhang, Jun, 2015. "Does individual investor trading impact firm valuation?," Journal of Corporate Finance, Elsevier, vol. 35(C), pages 120-135.
    13. Frino, Alex & Mollica, Vito & Webb, Robert I. & Zhang, Shunquan, 2017. "The impact of latency sensitive trading on high frequency arbitrage opportunities," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 91-102.
    14. Upson, James & Van Ness, Robert A., 2017. "Multiple markets, algorithmic trading, and market liquidity," Journal of Financial Markets, Elsevier, vol. 32(C), pages 49-68.
    15. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    16. Serbera, Jean-Philippe & Paumard, Pascal, 2016. "The fall of high-frequency trading: A survey of competition and profits," Research in International Business and Finance, Elsevier, vol. 36(C), pages 271-287.
    17. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    18. O’Hara, Maureen, 2015. "High frequency market microstructure," Journal of Financial Economics, Elsevier, vol. 116(2), pages 257-270.
    19. Nikolsko-Rzhevska, Olena & Nikolsko-Rzhevskyy, Alex & Black, Jeffrey R., 2020. "The life of U’s: Order revisions on NASDAQ," Journal of Banking & Finance, Elsevier, vol. 111(C).
    20. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).

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