IDEAS home Printed from https://ideas.repec.org/p/bdi/opques/qef_198_13.html
   My bibliography  Save this paper

High frequency trading: an overview

Author

Listed:
  • Alfonso Puorro

    (Bank of italy)

Abstract

This paper examines high-frequency trading systems, which were first developed in the US equity markets but have spread steadily to most asset classes on the main world financial markets. It analyzes the current regulatory and technological structures of the markets and describes the inefficiencies and informational advantages that high-frequency trading systems seek to exploit and the strategies they use. The paper concludes with an assessment of the positive and negative impacts of the presence of this new type of player on the overall quality of the financial markets.

Suggested Citation

  • Alfonso Puorro, 2013. "High frequency trading: an overview," Questioni di Economia e Finanza (Occasional Papers) 198, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_198_13
    as

    Download full text from publisher

    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2013-0198/QEF_198.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Didier SORNETTE & Susanne VON DER BECKE, 2011. "Crashes and High Frequency Trading," Swiss Finance Institute Research Paper Series 11-63, Swiss Finance Institute.
    2. Reginald D. Smith, 2010. "Is high-frequency trading inducing changes in market microstructure and dynamics?," Papers 1006.5490, arXiv.org, revised Sep 2010.
    3. Didier SORNETTE & Susanne VON DER BECKE, 2011. "Crashes and High Frequency Trading," Swiss Finance Institute Research Paper Series 11-64, Swiss Finance Institute.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    2. Virgilio, Gianluca, 2017. "Is high-frequency trading tiering the financial markets?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 158-171.
    3. Floris Laly & Mikael Petitjean, 2020. "Mini flash crashes: Review, taxonomy and policy responses," Bulletin of Economic Research, Wiley Blackwell, vol. 72(3), pages 251-271, July.
    4. Meynhardt, Timo & von Müller, Camillo, 2013. "„Wir wollen Werte schaffen für die Gesellschaft“ – Der Public Value im Spannungsfeld zwischen Aktienwert und Gemeinwohl. Eine Fallstudie am Beispiel der Deutsche Börse AG," ZögU - Zeitschrift für öffentliche und gemeinwirtschaftliche Unternehmen, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 36(2-3), pages 119-149.
    5. Alexandru Mandes, 2015. "Impact of inventory-based electronic liquidity providers within a high-frequency event- and agent-based modeling framework," MAGKS Papers on Economics 201515, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Didier Sornette & Peter Cauwels, 2014. "1980–2008: The Illusion of the Perpetual Money Machine and What It Bodes for the Future," Risks, MDPI, vol. 2(2), pages 1-29, April.
    7. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.
    8. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    9. Thomas H. McInish & Olena Nikolsko‐Rzhevska & Alex Nikolsko‐Rzhevskyy & Irina Panovska, 2020. "Fast and slow cancellations and trader behavior," Financial Management, Financial Management Association International, vol. 49(4), pages 973-996, December.
    10. Steffen, Viktoria, 2023. "A literature review on extreme price movements with reversal," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    11. 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).
    12. Gianluca Piero Maria Virgilio, 2019. "High-frequency trading: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 183-208, June.
    13. Chu, Gang & Zhang, Yongjie & Zhang, Xiaotao, 2021. "An analysis of impact of cancellation activity on market quality: Evidence from China," Economic Modelling, Elsevier, vol. 102(C).
    14. Kempf, Alexander & Mayston, Daniel & Gehde-Trapp, Monika & Yadav, Pradeep K., 2015. "Resiliency: A dynamic view of liquidity," CFR Working Papers 15-04, University of Cologne, Centre for Financial Research (CFR).
    15. Blasco, Natividad & Corredor, Pilar & Ferreruela, Sandra, 2017. "Can agents sensitive to cultural, organizational and environmental issues avoid herding?," Finance Research Letters, Elsevier, vol. 22(C), pages 114-121.
    16. Alexandru Mandes, 2020. "Impact of Electronic Liquidity Providers Within a High-Frequency Agent-Based Modeling Framework," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 407-450, February.
    17. Andrikopoulos, Panagiotis & Kallinterakis, Vasileios & Leite Ferreira, Mario Pedro & Verousis, Thanos, 2017. "Intraday herding on a cross-border exchange," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 25-36.
    18. Peter Lerner, 2015. "Patience vs. impatience of traders: Formation of the value-at-price distribution through competition for liquidity," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-30.
    19. AlShelahi, Abdullah & Saigal, Romesh, 2018. "Insights into the macroscopic behavior of equity markets: Theory and application," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 778-793.
    20. Reginald D. Smith, 2017. "Bitcoin Average Dormancy: A Measure of Turnover and Trading Activity," Papers 1712.10287, arXiv.org, revised Feb 2018.
    21. Bicchetti, David & Maystre, Nicolas Maystre, 2013. "The synchronized and long-lasting structural change on commodity markets: Evidence from high frequency data," Algorithmic Finance, IOS Press, vol. 2(3-4), pages 233-239.

    More about this item

    Keywords

    high frequency trading;

    JEL classification:

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bdi:opques:qef_198_13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bdigvit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.