IDEAS home Printed from https://ideas.repec.org/a/eme/sefpps/sef-02-2018-0066.html
   My bibliography  Save this article

Price formation in call auctions with insider information

Author

Listed:
  • Tobias Brünner

Abstract

Purpose - This study aims to investigate – theoretically and empirically – if call auctions incorporate asymmetric information into prices. Design/methodology/approach - First, this study introduces a new model of price formation in a call auction with insider information. In this call auction model, insider trading gives rise to an asymmetric information component of transaction costs. Next, this study estimates the model using 20 stocks from Euronext Paris and investigates if the asymmetric information component is present. Findings - The theoretical analysis reveals that call auctions incorporate asymmetric information into prices. The empirical analysis finds strong evidence for the asymmetric information component. Testable implications provide further support for the model. Practical implications - Call auctions have recently been proposed as an alternative to continuous limit order book markets to overcome problems associated with high-frequency trading. However, it is still an open question whether call auctions efficiently aggregate asymmetric information. The findings of this study imply that call auctions facilitate price discovery and, therefore, are a viable alternative to continuous limit order book markets. Originality/value - There is no generally accepted measure of trading costs for call auctions. Therefore, the measure introduced in this study is of great value to anyone who wants to quantify trading costs in call auctions, understand the determinants of trading costs in call auctions or compare trading costs and their components between continuous markets and call auctions. This study also contributes to the literature devoted to estimating the probability of information-based trading.

Suggested Citation

  • Tobias Brünner, 2019. "Price formation in call auctions with insider information," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 36(3), pages 408-426, July.
  • Handle: RePEc:eme:sefpps:sef-02-2018-0066
    DOI: 10.1108/SEF-02-2018-0066
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/SEF-02-2018-0066/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/SEF-02-2018-0066/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1108/SEF-02-2018-0066?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Yan Feng & Shulin Liu, 2024. "Research on Price Formation Based on Resource Optimization Allocation," Sustainability, MDPI, vol. 16(12), pages 1-20, June.

    More about this item

    Keywords

    Transaction costs; Informational efficiency; Asymmetric information; Bayesian econometrics; D82; G14; C11;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    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:eme:sefpps:sef-02-2018-0066. 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: Emerald Support (email available below). General contact details of provider: .

    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.