IDEAS home Printed from https://ideas.repec.org/p/bde/wpaper/1111.html
   My bibliography  Save this paper

Where is the value in high frequency trading?

Author

Listed:
  • Álvaro Cartea

    (Universidad Carlos III de Madrid)

  • José Penalva

    (Banco de España)

Abstract

We analyze the impact of high frequency trading in financial markets based on a model with three types of traders: liquidity traders, market makers, and high frequency traders. Our four main findings are: i) The price impact of the liquidity trades is higher in the presence of the high frequency trader and is increasing with the size of the trade. In particular, we show that the high frequency trader reduces (increases) the prices that liquidity traders receive when selling (buying) their equity holdings. ii) Although market makers also lose revenue to the high frequency trader in every trade, they are compensated for these losses by a higher liquidity discount. iii) High frequency trading increases the volatility of prices. iv) The volume of trades doubles as the high frequency trader intermediates all trades between the liquidity traders and market makers. This additional volume is a consequence of trades which are carefully tailored for surplus extraction and are neither driven by fundamentals nor is it noise trading. In equilibrium, high frequency trading and traditional market making coexist as competition drives down the profits for new high frequency traders while the presence of high frequency traders does not drive out traditional market makers.

Suggested Citation

  • Álvaro Cartea & José Penalva, 2011. "Where is the value in high frequency trading?," Working Papers 1111, Banco de España.
  • Handle: RePEc:bde:wpaper:1111
    as

    Download full text from publisher

    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/11/Fich/dt1111e.pdf
    File Function: First version, May 2011
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cespa, Giovanni & Foucault, Thierry, 2008. "Insiders-outsiders, transparency and the value of the ticker," CFS Working Paper Series 2008/39, Center for Financial Studies (CFS).
    2. Terrence Hendershott & Ryan Riordan, 2009. "Algorithmic Trading and Information," Working Papers 09-08, NET Institute, revised Aug 2009.
    3. Foucault, Thierry & Cespa, Giovanni, 2008. "Insiders-outsiders, transparency and the value of the ticker," HEC Research Papers Series 892, HEC Paris.
    4. Michael Kearns & Alex Kulesza & Yuriy Nevmyvaka, 2010. "Empirical Limitations on High Frequency Trading Profitability," Papers 1007.2593, arXiv.org, revised Sep 2010.
    5. 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.
    6. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    7. 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.
    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. J. Doyne Farmer & Spyros Skouras, 2013. "An ecological perspective on the future of computer trading," Quantitative Finance, Taylor & Francis Journals, vol. 13(3), pages 325-346, February.
    2. Ciamac C. Moallemi & Mehmet Sağlam, 2013. "OR Forum---The Cost of Latency in High-Frequency Trading," Operations Research, INFORMS, vol. 61(5), pages 1070-1086, October.
    3. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    4. Yacine Aït-Sahalia & Mehmet Saglam, 2013. "High Frequency Traders: Taking Advantage of Speed," NBER Working Papers 19531, National Bureau of Economic Research, Inc.
    5. Le, Anh Tu & Le, Thai-Ha & Liu, Wai-Man & Fong, Kingsley Y., 2020. "Multiple duration analyses of dynamic limit order placement strategies and aggressiveness in a low-latency market environment," International Review of Financial Analysis, Elsevier, vol. 72(C).
    6. Purba Mukerji & Christine Chung & Timothy Walsh & Bo Xiong, 2019. "The Impact of Algorithmic Trading in a Simulated Asset Market," JRFM, MDPI, vol. 12(2), pages 1-11, April.
    7. Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
    8. Robert J. Kauffman & Yuzhou Hu & Dan Ma, 2015. "Will high-frequency trading practices transform the financial markets in the Asia Pacific Region?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-27, December.
    9. George Jiang & Ingrid Lo & Giorgio Valente, 2014. "High-Frequency Trading around Macroeconomic News Announcements: Evidence from the U.S. Treasury Market," Staff Working Papers 14-56, Bank of Canada.
    10. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    11. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.
    12. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    13. Ya‐Kai Chang & Robin K. Chou, 2022. "Algorithmic trading and market quality: Evidence from the Taiwan index futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1837-1855, October.
    14. Cécile Bastidon, 2017. "Stock markets fragmentation, volatility and final investors," Annals of Finance, Springer, vol. 13(4), pages 435-451, November.
    15. 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.
    16. Murray, Hamish & Pham, Thu Phuong & Singh, Harminder, 2016. "Latency reduction and market quality: The case of the Australian Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 257-265.
    17. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    18. Angerer, Martin & Neugebauer, Tibor & Shachat, Jason, 2023. "Arbitrage bots in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 262-278.
    19. 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).
    20. Adrian, Tobias & Capponi, Agostino & Fleming, Michael & Vogt, Erik & Zhang, Hongzhong, 2020. "Intraday market making with overnight inventory costs," Journal of Financial Markets, Elsevier, vol. 50(C).

    More about this item

    Keywords

    high frequency traders; high frequency trading; flash trading; liquidity traders; institutional investors; market microstructure;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:bde:wpaper:1111. 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: Ángel Rodríguez. Electronic Dissemination of Information Unit. Research Department. Banco de España (email available below). General contact details of provider: https://edirc.repec.org/data/bdegves.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.