IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-00590283.html
   My bibliography  Save this paper

Optimal algorithmic trading and market microstructure

Author

Listed:
  • Mauricio Labadie

    (CAMS - Centre d'Analyse et de Mathématique sociales - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique)

  • Charles-Albert Lehalle

    (Head of Quantitative Research - CALYON group)

Abstract

The efficient frontier is a core concept in Modern Portfolio Theory. Based on this idea, we will construct optimal trading curves for different types of portfolios. These curves correspond to the algorithmic trading strategies that minimize the expected transaction costs, i.e. the joint effect of market impact and market risk. We will study five portfolio trading strategies. For the first three (single-asset, general multi-asseet and balanced portfolios) we will assume that the underlyings follow a Gaussian diffusion, whereas for the last two portfolios we will suppose that there exists a combination of assets such that the corresponding portfolio follows a mean-reverting dynamics. The optimal trading curves can be computed by solving an N-dimensional optimization problem, where N is the (pre-determined) number of trading times. We will solve the recursive algorithm using the "shooting method", a numerical technique for differential equations. This method has the advantage that its corresponding equation is always one-dimensional regardless of the number of trading times N. This novel approach could be appealing for high-frequency traders and electronic brokers.

Suggested Citation

  • Mauricio Labadie & Charles-Albert Lehalle, 2010. "Optimal algorithmic trading and market microstructure," Working Papers hal-00590283, HAL.
    • Handle: RePEc:hal:wpaper:hal-00590283
    Note: View the original document on HAL open archive server: https://hal.science/hal-00590283v2
    as

    Download full text from publisher

    File URL: https://hal.science/hal-00590283v2/document
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hagströmer, Björn, 2021. "Bias in the effective bid-ask spread," Journal of Financial Economics, Elsevier, vol. 142(1), pages 314-337.
    2. Taiga Saito & Takanori Adachi & Teruo Nakatsuma & Akihiko Takahashi & Hiroshi Tsuda & Naoyuki Yoshino, 2018. "Trading and Ordering Patterns of Market Participants in High Frequency Trading Environment: Empirical Study in the Japanese Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(3), pages 179-220, September.
    3. David Saltiel & Eric Benhamou, 2018. "Trade Selection with Supervised Learning and OCA," Papers 1812.04486, arXiv.org.

    More about this item

    Keywords

    quantitative finance; optimal trading; algorithmic trading; systematic trading; market microstructure;
    All these keywords.

    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:hal:wpaper:hal-00590283. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.